{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.0.0\n",
      "sys.version_info(major=3, minor=7, micro=5, releaselevel='final', serial=0)\n",
      "numpy 1.16.4\n",
      "pandas 0.25.3\n",
      "sklearn 0.22\n",
      "tensorflow 2.0.0\n",
      "tensorflow_core.keras 2.2.4-tf\n",
      "Training Images ->  35280\n",
      "Validation Images ->  1008\n",
      "Test Images ->  56\n"
     ]
    }
   ],
   "source": [
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "import sklearn\n",
    "import sys\n",
    "import tensorflow as tf\n",
    "import time\n",
    "import random\n",
    "import pathlib\n",
    "\n",
    "from tensorflow import keras\n",
    "\n",
    "print(tf.__version__)\n",
    "print(sys.version_info)\n",
    "for module in np, pd, sklearn, tf, keras:\n",
    "    print(module.__name__, module.__version__)\n",
    "\n",
    "\n",
    "training_path = pathlib.Path('./training')\n",
    "validation_path = pathlib.Path('./valid')\n",
    "test_path = pathlib.Path('./test')\n",
    "\n",
    "train_image_paths = list(training_path.glob('*/*'))  \n",
    "valid_image_paths = list(validation_path.glob('*/*'))  \n",
    "test_image_paths = list(test_path.glob('*/'))  \n",
    "\n",
    "train_image_paths = [str(path) for path in train_image_paths]\n",
    "valid_image_paths = [str(path) for path in valid_image_paths]\n",
    "test_image_paths = [str(path) for path in test_image_paths]\n",
    "\n",
    "random.shuffle(train_image_paths)\n",
    "random.shuffle(valid_image_paths)\n",
    "random.shuffle(test_image_paths)\n",
    "\n",
    "train_image_count = len(train_image_paths)\n",
    "valid_image_count = len(valid_image_paths)\n",
    "test_image_count = len(test_image_paths)\n",
    "\n",
    "print(\"Training Images -> \", train_image_count)\n",
    "print(\"Validation Images -> \", valid_image_count)\n",
    "print(\"Test Images -> \", test_image_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['training\\\\Olaf\\\\450.jpg',\n",
       " 'training\\\\Lux\\\\336.jpg',\n",
       " 'training\\\\Syndra\\\\165.jpg',\n",
       " 'training\\\\Braum\\\\149.jpg',\n",
       " 'training\\\\KhaZix\\\\605.jpg']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_image_paths[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['valid\\\\Azir\\\\10.jpg',\n",
       " 'valid\\\\Karma\\\\10.jpg',\n",
       " 'valid\\\\Nautilus\\\\10.jpg',\n",
       " 'valid\\\\Neeko\\\\1.jpg',\n",
       " 'valid\\\\Nautilus\\\\17.jpg']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "valid_image_paths[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['test\\\\Diana.jpg',\n",
       " 'test\\\\Amumu.jpg',\n",
       " 'test\\\\Volibear.jpg',\n",
       " 'test\\\\Taric.jpg',\n",
       " 'test\\\\Sion.jpg']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_image_paths[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Aatrox',\n",
       " 'Amumu',\n",
       " 'Annie',\n",
       " 'Ashe',\n",
       " 'Azir',\n",
       " 'Brand',\n",
       " 'Braum',\n",
       " 'Diana',\n",
       " 'DrMundo',\n",
       " 'Ezreal',\n",
       " 'Ivern',\n",
       " 'Janna',\n",
       " 'Jax',\n",
       " 'Karma',\n",
       " 'KhaZix',\n",
       " 'Kindred',\n",
       " 'KogMaw',\n",
       " 'LeBlanc',\n",
       " 'Leona',\n",
       " 'Lucian',\n",
       " 'Lux',\n",
       " 'Malphite',\n",
       " 'Malzahar',\n",
       " 'Maokai',\n",
       " 'MasterYi',\n",
       " 'Nami',\n",
       " 'Nasus',\n",
       " 'Nautilus',\n",
       " 'Neeko',\n",
       " 'Nocturne',\n",
       " 'Olaf',\n",
       " 'Ornn',\n",
       " 'Qiyana',\n",
       " 'RekSai',\n",
       " 'Renekton',\n",
       " 'Senna',\n",
       " 'Singed',\n",
       " 'Sion',\n",
       " 'Sivir',\n",
       " 'Skarner',\n",
       " 'Soraka',\n",
       " 'Syndra',\n",
       " 'Taliyah',\n",
       " 'Taric',\n",
       " 'Thresh',\n",
       " 'Twitch',\n",
       " 'Varus',\n",
       " 'Vayne',\n",
       " 'Veigar',\n",
       " 'Vladimir',\n",
       " 'Volibear',\n",
       " 'Warwick',\n",
       " 'Yasuo',\n",
       " 'Yorick',\n",
       " 'Zed',\n",
       " 'Zyra']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_names = sorted(item.name for item in training_path.glob('*/') if item.is_dir())\n",
    "label_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training\\Olaf\\450.jpg  --->   Olaf\n",
      "training\\Lux\\336.jpg  --->   Lux\n",
      "training\\Syndra\\165.jpg  --->   Syndra\n",
      "training\\Braum\\149.jpg  --->   Braum\n",
      "training\\KhaZix\\605.jpg  --->   KhaZix\n"
     ]
    }
   ],
   "source": [
    "training_image_labels = [pathlib.Path(path).parent.name for path in train_image_paths]\n",
    "for image, label in zip(train_image_paths[:5], training_image_labels[:5]):\n",
    "    print(image, ' --->  ', label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_labels_info = []\n",
    "for image_path, label in zip(train_image_paths, training_image_labels):\n",
    "    train_labels_info.append((image_path, label))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('training\\\\Olaf\\\\450.jpg', 'Olaf'),\n",
      " ('training\\\\Lux\\\\336.jpg', 'Lux'),\n",
      " ('training\\\\Syndra\\\\165.jpg', 'Syndra'),\n",
      " ('training\\\\Braum\\\\149.jpg', 'Braum'),\n",
      " ('training\\\\KhaZix\\\\605.jpg', 'KhaZix')]\n"
     ]
    }
   ],
   "source": [
    "import pprint\n",
    "pprint.pprint(train_labels_info[:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "valid\\Azir\\10.jpg  --->   Azir\n",
      "valid\\Karma\\10.jpg  --->   Karma\n",
      "valid\\Nautilus\\10.jpg  --->   Nautilus\n",
      "valid\\Neeko\\1.jpg  --->   Neeko\n",
      "valid\\Nautilus\\17.jpg  --->   Nautilus\n"
     ]
    }
   ],
   "source": [
    "valid_image_labels = [pathlib.Path(path).parent.name for path in valid_image_paths]\n",
    "for image, label in zip(valid_image_paths[:5], valid_image_labels[:5]):\n",
    "    print(image, ' --->  ', label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "valid_labels_info = []\n",
    "for image_path, label in zip(valid_image_paths, valid_image_labels):\n",
    "    valid_labels_info.append((image_path, label))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('valid\\\\Azir\\\\10.jpg', 'Azir'),\n",
      " ('valid\\\\Karma\\\\10.jpg', 'Karma'),\n",
      " ('valid\\\\Nautilus\\\\10.jpg', 'Nautilus'),\n",
      " ('valid\\\\Neeko\\\\1.jpg', 'Neeko'),\n",
      " ('valid\\\\Nautilus\\\\17.jpg', 'Nautilus')]\n"
     ]
    }
   ],
   "source": [
    "pprint.pprint(valid_labels_info[:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test\\Diana.jpg  --->   Diana\n",
      "test\\Amumu.jpg  --->   Amumu\n",
      "test\\Volibear.jpg  --->   Volibear\n",
      "test\\Taric.jpg  --->   Taric\n",
      "test\\Sion.jpg  --->   Sion\n"
     ]
    }
   ],
   "source": [
    "test_image_labels = [path.split('\\\\')[1].split('.')[0] for path in test_image_paths]\n",
    "for image, label in zip(test_image_paths[:5], test_image_labels[:5]):\n",
    "    print(image, ' --->  ', label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_labels_info = []\n",
    "for image_path, label in zip(test_image_paths, test_image_labels):\n",
    "    test_labels_info.append((image_path, label))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                  filepath   class\n",
      "0    training\\Olaf\\450.jpg    Olaf\n",
      "1     training\\Lux\\336.jpg     Lux\n",
      "2  training\\Syndra\\165.jpg  Syndra\n",
      "3   training\\Braum\\149.jpg   Braum\n",
      "4  training\\KhaZix\\605.jpg  KhaZix\n",
      "                filepath     class\n",
      "0      valid\\Azir\\10.jpg      Azir\n",
      "1     valid\\Karma\\10.jpg     Karma\n",
      "2  valid\\Nautilus\\10.jpg  Nautilus\n",
      "3      valid\\Neeko\\1.jpg     Neeko\n",
      "4  valid\\Nautilus\\17.jpg  Nautilus\n",
      "            filepath     class\n",
      "0     test\\Diana.jpg     Diana\n",
      "1     test\\Amumu.jpg     Amumu\n",
      "2  test\\Volibear.jpg  Volibear\n",
      "3     test\\Taric.jpg     Taric\n",
      "4      test\\Sion.jpg      Sion\n"
     ]
    }
   ],
   "source": [
    "train_df = pd.DataFrame(train_labels_info)\n",
    "valid_df = pd.DataFrame(valid_labels_info)\n",
    "test_df = pd.DataFrame(test_labels_info)\n",
    "\n",
    "train_df.columns = valid_df.columns =test_df.columns = ['filepath', 'class']\n",
    "\n",
    "print(train_df.head())\n",
    "print(valid_df.head())\n",
    "print(test_df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 35280 validated image filenames belonging to 56 classes.\n",
      "Found 1008 validated image filenames belonging to 56 classes.\n",
      "Found 56 validated image filenames belonging to 56 classes.\n"
     ]
    }
   ],
   "source": [
    "height = 64\n",
    "width = 64\n",
    "channels = 3\n",
    "batch_size = 64\n",
    "num_classes = 56\n",
    "\n",
    "train_datagen = keras.preprocessing.image.ImageDataGenerator(\n",
    "    #像素值 都除以255\n",
    "    rescale = 1./255,\n",
    "    # 图片随机旋转 (5度以内)\n",
    "    rotation_range = 5,\n",
    "    # 图片左右位移  20%限度以内\n",
    "    width_shift_range = 0.2,\n",
    "    # 图片上下位移  20%限度以内\n",
    "    height_shift_range = 0.2,\n",
    "    # 图像剪切强度\n",
    "    shear_range = 0.2,\n",
    "    # 图像缩放强度\n",
    "    zoom_range = 0.2,\n",
    "    # 是否水平翻转\n",
    "    horizontal_flip = False,\n",
    "    # 放大缩小吼， 像素填充方式\n",
    "    fill_mode = 'nearest',\n",
    ")\n",
    "\n",
    "train_generator = train_datagen.flow_from_dataframe(train_df, directory = './',\n",
    "                                                    x_col = 'filepath',\n",
    "                                                    y_col = 'class',\n",
    "                                                    classes = label_names,\n",
    "                                                    target_size = (height, width),\n",
    "                                                    batch_size = batch_size,\n",
    "                                                    seed = 2333,\n",
    "                                                    shuffle = True,\n",
    "                                                    class_mode = \"categorical\")\n",
    "\n",
    "valid_datagen = keras.preprocessing.image.ImageDataGenerator(\n",
    "    rescale = 1./255,\n",
    ")\n",
    "valid_generator = valid_datagen.flow_from_dataframe(valid_df, directory = './',\n",
    "                                                    x_col = 'filepath',\n",
    "                                                    y_col = 'class',\n",
    "                                                    classes = label_names,\n",
    "                                                    target_size = (height, width),\n",
    "                                                    batch_size = batch_size,\n",
    "                                                    seed = 2333,\n",
    "                                                    shuffle = True,\n",
    "                                                    class_mode = \"categorical\")\n",
    "\n",
    "test_datagen = keras.preprocessing.image.ImageDataGenerator(\n",
    "    rescale = 1./255,\n",
    ")\n",
    "test_generator = test_datagen.flow_from_dataframe(test_df, directory = './',\n",
    "                                                    x_col = 'filepath',\n",
    "                                                    y_col = 'class',\n",
    "                                                    classes = label_names,\n",
    "                                                    target_size = (height, width),\n",
    "                                                    batch_size = batch_size,\n",
    "                                                    seed = 2333,\n",
    "                                                    shuffle = True,\n",
    "                                                    class_mode = \"categorical\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Generator Sample ->  35280\n",
      "Validation Generator Sample ->  1008\n",
      "Test Generator Sample ->  56\n"
     ]
    }
   ],
   "source": [
    "train_num = train_generator.samples\n",
    "valid_num = valid_generator.samples\n",
    "test_num = test_generator.samples\n",
    "\n",
    "print(\"Training Generator Sample -> \", train_num)\n",
    "print(\"Validation Generator Sample -> \", valid_num)\n",
    "print(\"Test Generator Sample -> \", test_num)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(64, 64, 64, 3) (64, 56)\n",
      "[[0. 0. 0. ... 0. 0. 0.]\n",
      " [0. 0. 1. ... 0. 0. 0.]\n",
      " [0. 0. 0. ... 0. 0. 0.]\n",
      " ...\n",
      " [0. 0. 0. ... 0. 0. 0.]\n",
      " [0. 0. 0. ... 0. 0. 0.]\n",
      " [0. 0. 0. ... 0. 0. 0.]]\n",
      "(64, 64, 64, 3) (64, 56)\n",
      "[[0. 0. 1. ... 0. 0. 0.]\n",
      " [0. 0. 0. ... 0. 0. 0.]\n",
      " [0. 0. 0. ... 0. 0. 0.]\n",
      " ...\n",
      " [0. 0. 0. ... 0. 0. 0.]\n",
      " [0. 0. 0. ... 0. 0. 0.]\n",
      " [0. 0. 0. ... 0. 0. 0.]]\n"
     ]
    }
   ],
   "source": [
    "for i in range(2):\n",
    "    x, y = train_generator.next()\n",
    "    print(x.shape, y.shape)\n",
    "    print(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d (Conv2D)              (None, 64, 64, 16)        448       \n",
      "_________________________________________________________________\n",
      "conv2d_1 (Conv2D)            (None, 64, 64, 16)        2320      \n",
      "_________________________________________________________________\n",
      "max_pooling2d (MaxPooling2D) (None, 32, 32, 16)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_2 (Conv2D)            (None, 32, 32, 32)        4640      \n",
      "_________________________________________________________________\n",
      "conv2d_3 (Conv2D)            (None, 32, 32, 32)        9248      \n",
      "_________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2 (None, 16, 16, 32)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_4 (Conv2D)            (None, 16, 16, 64)        18496     \n",
      "_________________________________________________________________\n",
      "conv2d_5 (Conv2D)            (None, 16, 16, 64)        36928     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2 (None, 8, 8, 64)          0         \n",
      "_________________________________________________________________\n",
      "flatten (Flatten)            (None, 4096)              0         \n",
      "_________________________________________________________________\n",
      "dense (Dense)                (None, 128)               524416    \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 56)                7224      \n",
      "=================================================================\n",
      "Total params: 603,720\n",
      "Trainable params: 603,720\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = keras.models.Sequential([\n",
    "    keras.layers.Conv2D(filters=16, kernel_size = 3, padding='same',\n",
    "                       activation = 'selu', input_shape = [width, height, channels]),\n",
    "    keras.layers.Conv2D(filters=16, kernel_size = 3, \n",
    "                        padding='same', activation = 'selu'),\n",
    "    keras.layers.MaxPool2D(pool_size=2),\n",
    "    \n",
    "    keras.layers.Conv2D(filters=32, kernel_size = 3, padding='same',\n",
    "                       activation = 'selu', input_shape = [width, height, channels]),\n",
    "    keras.layers.Conv2D(filters=32, kernel_size = 3, \n",
    "                        padding='same', activation = 'selu'),\n",
    "    keras.layers.MaxPool2D(pool_size=2),\n",
    "    \n",
    "    keras.layers.Conv2D(filters=64, kernel_size = 3, \n",
    "                        padding='same', activation = 'selu'),\n",
    "    keras.layers.Conv2D(filters=64, kernel_size = 3, \n",
    "                        padding='same', activation = 'selu'),\n",
    "    keras.layers.MaxPool2D(pool_size=2),\n",
    "    \n",
    "    keras.layers.Flatten(),\n",
    "    keras.layers.Dense(128, activation = 'selu'),\n",
    "    \n",
    "    keras.layers.Dense(num_classes, activation = 'softmax')\n",
    "])\n",
    "\n",
    "model.compile(loss=\"categorical_crossentropy\",\n",
    "             optimizer = \"adam\", metrics = ['accuracy'])\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "551/551 [==============================] - 64s 116ms/step - loss: 0.7066 - accuracy: 0.8019 - val_loss: 0.2167 - val_accuracy: 0.9229\n",
      "Epoch 2/20\n",
      "551/551 [==============================] - 65s 117ms/step - loss: 0.1996 - accuracy: 0.9412 - val_loss: 0.2012 - val_accuracy: 0.9396\n",
      "Epoch 3/20\n",
      "551/551 [==============================] - 57s 104ms/step - loss: 0.1372 - accuracy: 0.9623 - val_loss: 0.0792 - val_accuracy: 0.9719\n",
      "Epoch 4/20\n",
      "551/551 [==============================] - 59s 106ms/step - loss: 0.1191 - accuracy: 0.9674 - val_loss: 0.0177 - val_accuracy: 0.9948\n",
      "Epoch 5/20\n",
      "551/551 [==============================] - 58s 106ms/step - loss: 0.1127 - accuracy: 0.9707 - val_loss: 0.0324 - val_accuracy: 0.9865\n",
      "Epoch 6/20\n",
      "551/551 [==============================] - 62s 113ms/step - loss: 0.0919 - accuracy: 0.9783 - val_loss: 0.0622 - val_accuracy: 0.9802\n",
      "Epoch 7/20\n",
      "551/551 [==============================] - 59s 106ms/step - loss: 0.0997 - accuracy: 0.9768 - val_loss: 0.0302 - val_accuracy: 0.9906\n",
      "Epoch 8/20\n",
      "551/551 [==============================] - 57s 103ms/step - loss: 0.1106 - accuracy: 0.9769 - val_loss: 0.0116 - val_accuracy: 0.9969\n",
      "Epoch 9/20\n",
      "551/551 [==============================] - 57s 103ms/step - loss: 0.1052 - accuracy: 0.9776 - val_loss: 0.0034 - val_accuracy: 0.9990\n",
      "Epoch 10/20\n",
      "551/551 [==============================] - 62s 113ms/step - loss: 0.0924 - accuracy: 0.9817 - val_loss: 0.0309 - val_accuracy: 0.9927\n",
      "Epoch 11/20\n",
      "551/551 [==============================] - 57s 104ms/step - loss: 0.1154 - accuracy: 0.9789 - val_loss: 0.0227 - val_accuracy: 0.9927\n",
      "Epoch 12/20\n",
      "551/551 [==============================] - 56s 102ms/step - loss: 0.1103 - accuracy: 0.9812 - val_loss: 0.0342 - val_accuracy: 0.9885\n",
      "Epoch 13/20\n",
      "551/551 [==============================] - 56s 101ms/step - loss: 0.0920 - accuracy: 0.9849 - val_loss: 0.0095 - val_accuracy: 0.9969\n",
      "Epoch 14/20\n",
      "551/551 [==============================] - 57s 103ms/step - loss: 0.1402 - accuracy: 0.9798 - val_loss: 0.0849 - val_accuracy: 0.9865\n",
      "Epoch 15/20\n",
      "551/551 [==============================] - 57s 104ms/step - loss: 0.1158 - accuracy: 0.9839 - val_loss: 0.0330 - val_accuracy: 0.9958\n",
      "Epoch 16/20\n",
      "551/551 [==============================] - 56s 101ms/step - loss: 0.1817 - accuracy: 0.9768 - val_loss: 0.0268 - val_accuracy: 0.9979\n",
      "Epoch 17/20\n",
      "551/551 [==============================] - 57s 103ms/step - loss: 0.1631 - accuracy: 0.9820 - val_loss: 0.0455 - val_accuracy: 0.9937\n",
      "Epoch 18/20\n",
      "551/551 [==============================] - 56s 102ms/step - loss: 0.1295 - accuracy: 0.9859 - val_loss: 0.0062 - val_accuracy: 0.9979\n",
      "Epoch 19/20\n",
      "551/551 [==============================] - 56s 102ms/step - loss: 0.1544 - accuracy: 0.9840 - val_loss: 0.0097 - val_accuracy: 0.9979\n",
      "Epoch 20/20\n",
      "551/551 [==============================] - 56s 101ms/step - loss: 0.1323 - accuracy: 0.9866 - val_loss: 0.0345 - val_accuracy: 0.9927\n"
     ]
    }
   ],
   "source": [
    "epochs = 20\n",
    "#因为数据是generator 产生的 所以不能用fit函数\n",
    "history = model.fit_generator(train_generator, steps_per_epoch=train_num // batch_size,\n",
    "                             epochs=epochs, validation_data=valid_generator,\n",
    "                             validation_steps=valid_num//batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_learning_curves(history, label, epochs, min_value, max_value):\n",
    "    data = {}\n",
    "    data[label] = history.history[label]\n",
    "    data['val_'+label] = history.history['val_' + label]\n",
    "    \n",
    "    pd.DataFrame(data).plot(figsize = (8,5))\n",
    "    plt.grid(True)\n",
    "    plt.axis([0, epochs, min_value, max_value])\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_learning_curves(history, 'accuracy', epochs, 0, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_learning_curves(history, 'loss', epochs, 0, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_and_preprocess_single_img(path):\n",
    "    # read the img through file path\n",
    "    image = tf.io.read_file(path)  \n",
    "    image = tf.image.decode_jpeg(image, channels=3)\n",
    "    # 原始图片大小为(128, 128, 3)，重设为(64, 64)\n",
    "    image = tf.image.resize(image, [64, 64])  \n",
    "    image = tf.cast(image, tf.float32) / 255.0  # 归一化到[0,1]范围\n",
    "    image = np.expand_dims(image, axis = 0) # since you have batch_size, so you need to expand your image\n",
    "    return image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def evaluate_single_pic(path, show=False):\n",
    "    \n",
    "    if show:\n",
    "        import matplotlib.image as mpimg\n",
    "        plt.imshow(mpimg.imread(path))\n",
    "    image = load_and_preprocess_single_img(path)\n",
    "    predict_result = model.predict(image)\n",
    "    print(\"This is\", label_names[np.argmax(predict_result, axis=1)[0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is Olaf\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "test_pic_path = \"./test.jpg\"\n",
    "evaluate_single_pic(test_pic_path, True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is Aatrox\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "test_pic_path2 = \"./card.jpg\"\n",
    "evaluate_single_pic(test_pic_path2, True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is Twitch\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "test_pic_path3 = \"./5.png\"\n",
    "evaluate_single_pic(test_pic_path3, True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is Sion\n"
     ]
    },
    {
     "data": {
      "image/png": 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C63z4aYmmP2BR3NNlUblFYuXvalEJtSv/AMCTcT7i5WBK+EqtWg5UVtkltwuDBGbNJ4jglB24iVMj3vm54EmNAZt2h6WxLCjq9gOknnYDVJiMwxP+KYk4KsLJSYst5tBJAs2SYFaz3TSdviwphbYgGj25PJa8rain8vhj0otFB5bWXt3SbHFwL11WnWapd5X37bQC8lGQbkx0outrcD5G47AMsHlJgm6yOc9/SgosJQnlLoa/Rjwy9KLvkpjDeVhbD+ilQ61CzavEYZe4tFljgHXzSpCIE0I42N3Do08eAAAOd0Pqr8+g7ZT3IEdMmxbcV1qzUVP5e7i3utfTiSApx56k73zq7U8LbyZp1mwuyJp4fkNIFRKorLLKzrCLgwTO8Fo++ce8tqNxPU3maZ0qwBubYb23skKVXBb1nAxCIPD5LoU4dkPqp3sc1t/Hh10eszx2tE0EGxTwsfVtPkNc4mfympNCJbBK/eiQDB4VybmSc9asCCfZbS4kcNqknj7R8pYN0oElTDFhOrNdF6oJ5x7TsxVzC9R4SOXr2HuZV8tmC4JSZBNMBBtNjyi2ayziuXkrBPOEvCSqcvWqRFJDkK+dCMpIDHV7K6C/Z0+3sPM4xAAKorEm1/btBuXDMqWYY0EPjVWoQiIrQgIq4prPgiu9F6OcOMMapzjLtHeS+lSsJAkIulNQxaxVSKCyyi65XRwkMGtzNGH7ILyfEFGUeqs3GlgjArh95xUAwI1boYy3s0zZciIFkTReI/11l9LZjx8FT7CzE5DByUlIBSqdN52yfNdEMWN4UspPuTnWZrnmjWMZpZ5+fN1pkU/JiUpSf6koR1qm+yl06kWSMU9ENKIYgEqG1dylSKL95bl4TUnZblnLomvkmApnsRGPOK6g66vT63ZWgyffII16lWv727cDnXqL6bshI/jmjknK6rHc96QXUN6znXDPu4dBEm0yHBiRSyK3bcZI6kzzpmt254UMRJMOY5V4y7RIkGI8Tad461O89qJmO3afde8szRKd5LxeBhUSqKyyS24XBgl4tzAXUGYBzJLINnOz9XoTOYt1psqV8nVnJXiNJWYJWswVC0XcvvUaAODKZiggevBRKAja2Qm8gd4JRUFPgjcZTwYcHBGBS9z+3CjL68iTJ3pJ8ogjxamVS/2Y9DJfKBRvTw8RzCAWlChFHkyiGEvsBiVyUJfchTLeoYV6dNiy+MfGGIuK5HWVIjcNnY1YhKR1twQ8VL4sEdQNCsI0eQ8ltHpAMtWYmZ69vVD2rTiPJNhP1JiGFHBxAzrNBpZYtCUElCet0UyghffMBD+432CkdmwS+4zRmvOLkEGMBLx5cVd+V3PH+ESbhWggrbzB0nVltNRtS0Vzi6xCApVVdsntgiABR+93XgHRgi2flNNJgQOy64Yj5t6JCBpNUkOJBJTXPT44jo6oMtw1ZhM818AnpNEe0yOe9EgvHlLKi7GCIo0VzJhPgwSGCIroG4uxhC43RhIp+2zh9075SEigpLeywIV58A5z66ucjyJj9oRya5Doq4qdFD2viT4dvr9MoVa1c1tZVVuzJWQueK79veDJNS+rPHejQXFOZnTU8kwNX7tc66vxzIBt6QZc+4s2qly/YgVNXrOKfJY7bayyYEqevmzuOtGMcX5UFJZxGijmKvZnkgEqp/30e+OR3rtZhispxvT0q+uB37BJ4ZucJetLSyxRVyNc3svBoHfqOWUVEqissktuFwQJhOeen4tip1Hv0787J9qIkun18KMg2HHC9eIzioZcvxZyy10WDpVttBhB5vvyturCu7kRnr7tVvBSh4fP+X02RPFqxjGdl3xOxi9vY17HkgFJVmCOWB5zEl7E0gYdYicKrDSIgNbJriskWEJvc9Kl12UrOCGKVZZFv/LqPW5DtuYa5duWllUkNcCTx4Gdd/1akF8bEWUoFy8Ox3NKu/WJCHSvJCIrj6/vj0dx3KbGa20w0q/vaTudTK3RKixvzziOagW4/hYCGMrbKhZQxHGdkvOQ8k2SV4qhWKak/ECorNle5paMSNZtTArGUmrhXuSMiVgcYxwL0qZWIYHKKrvkdiGQgEdgnulpWSKChIWmCHyhN1JudIHMmHt8knOtfrgbcsInbKj5lI081Oqs11Nb7+AJ1MJL+W5FsNWyW+yzq1eD6MQJswaHh4Gt1u+fYFqoxZSGm1D7kpx5ST48Pa9/Xin1eeZnzpHossytaTO2tDrhOlvR79dfC1kUeaGxKPH0Vm0iB4mz3LsXeBq3boVcfoNNSNRA5mD/CCMKrr7P5qWq5GyxDbrEYY84twcH+9GYl5dZ6cnXFmlPOPRZnbx/NblRVSfjGWNfwBdxebaqJmt5/B0xJgfDYfRap5yr40hcvi/TJ+G4zIRcvR6QpjIevZOejV9RfzXM2d8P82EZHStVD4cWt6F2TrlyhQQqq+yS24VAAqGUrGbMMdWyqx5fbktP1wnXn5LXmg7ltR1Mrcl4+HxCsydYn5HjPj23GmPqKeu4fnQQMy5slXs+OgpPXYmPKHetlmmrq4GnXqvVjJs+tjVZkgtOiyLmGoPgVCuZY58lNhDHISzToNp77jXiHG/RK0uA9AZjKeJbXKH4aZ+Q4Bmbs6hx6Xt/FlqUqyZB7bskVjIeTfDBh4GT8f6774SxMK8t7r+876B3zM+pbcAL7xt3IYy9bq3CxHIM76ft2Av+NoSwmvW6IQBlj6wprlqOs6qyp7jDWG3dFJcSW09r+/B+IRYs92sSMd16JcRKvvCjQbq+yWYmh2yHt/P0KU7YfGbKezKZMG7DzNWYDW0lR2ciGtaw9ewfSIUEKqvskttnRgLOuXsA/icANxFW6d/w3v+Wc24TwO8AuA/gAYBf8t7vn30sIK/XcPVKWA8ppzxVfpdPvA5biF1/5T4AYEQG2AfvBm8zHPRLBlcaYec/pBCkNa3WlXXm//WEVtWcPemJDDQmPT8LT645eQijcThuu71kTTclUy4UkraOTmMG5+WUPw8zRpoYcOZF4tfdg5BV2SGSanDePBmY2w9DY9YuI/HKTStPrvW2ag3yhDE4BdDjmn9CKa8ePf5kHN5vkiFXFHGsRPe4bI8ezt3ntsOMzgpjBsoKWFwkU21CyQpUExWpD2ncA8aMVJcw0XzpWEndgxV6iHHIdfmtuyFb8uWv/gQA4N6r98MYqHPxycNQ0Sh+y9LSGjLGKZTxAvP+1nyXcZYe0emgH9e3vMwqwgmA/8x7/8MAfhrAv++c+xEAvw7gm977twB8k68rq6yyC2qfGQl477cAbPHfx865dwDcAfA1AD/L3X4bwO8D+LWzjpVnNayurFsbcT1lS/ZV8E7K6U/ovVV9VzjlS6eWr5ZpjScWlaz0xorQK79LNRpGaxstNYeIvXKZX7dwMABgiao2k8nEvIbO3eiHY+4zui1Kt+IOMwcPm6RJxlx2IY08fxbgwHNM5zwbPb+EUxUl5z0ZkpnZpHe9xlbuV68FHsDqWoiNLLGJywl5GB+w0coHDz4O54U3ZmBBtaKxWJhqo14P86McvWTg9TsQ2hhxvoupWqLF2QJ591ILgPdeoqHwph+gKL+avo5HrAqUpqLVQkgwlJwDrunbZB6K1ffaF74IALjLhjNSuhpyjAfH4ZrFdJ0QUY5HhRVD6lwSyS2Zo2z9pqavQjbTItouss8lMOicuw/gqwC+BeAGHxDw3m85564v+M7XAXwdAGqE3pVVVtk/fnvhh4BzbhnA3wbwH3vvjz5tLtt7/w0A3wCA5ZUNf+XKtZK/ridzJg2+8KSbsKb/8OiAB2FEm16qudSG59N9yMyBWGN1HkPVYfL4cqITnnPCnPVY60oXnuzSrVOTCTHstO7Pa3xd1+ua/VtxBKke6ZxdahUMFStIotXzYf8FSECfntNuavYYSdGfJVNyY9WFB/MyEdGaJMjp+Vf42lh3qv0nUrjGzM49SrSP2FGlzjqBWha2Hz5+iOMBNRs4CEm1q4pwTXUGjfD+gJH5Ibd93mtVDY6IBKxBCu+tuAktViU2da+kFJxnmOSM/ZAnUlAqXN7Yqf03x99sht/FykZgVN68F6L9V28E/sgG25ddYf6/ztjR8XFAtfuM/PdPwjX0uuH3Ku7EaDQ2RFR2ieVvdRJfp2JnVq9g7ejOXvW/UHbAOVdHeAD8De/93+Hb2865W/z8FoCdFzlHZZVV9nLtRbIDDsB/D+Ad7/1/O/PR/w7gVwD8Jre/d96xMufY+DGuq8+ccvWKXIcnn0+QgbxaXsvRZES4MB45n6yMFUj11ZRg0ig5XeMkieBLfVf54lYreHV59yyLOd95nqPO3Ljl3pkjz0hmaLTC6+OjEIFX9kBr3PNUYktLWWnnfy/lrKdKQh2OdZ1r3GV6zRbnY5mef8BGKPvU9fOc38mtUKNxwipNces7jPS/ToTwaGcLe092OQjm/60SUToRVIwmMhArUZmGE0bNxe14/jzUIggNKgNUKjTFtSaZ4kUuK+Udra4/ZvgJAbQ6IdZx/Wa4zjuvhuu5weh/g4zSMb3z4yfBF+p3OByGMfUZK5lyfsZ9Zh/ILRkPB9b8dUquymjEeg1mx1Q1KaQDa3qqMZ/9Z/4iy4GfAfBvAviOc+6P+d5/ifDH/7vOuV8F8AmAX3yBc1RWWWUv2V4kO/APsDge/XM/yLEmkzH2n28ZB9q02unNvVh/ep1U5SnKW+S1iP0FAI6P9iERgXLKxh83vrU6E4nZFZ6m/SJmDgoZSNm2bu2mtP7X/qWnkicTalBFouoPaoonHNGzkWlY1rDzcuNExOdjYh9yzpvMhiwzJtBSVyDdmxE9PdfKIzIDl6n3d19r4s2wRu53AxLY2w85bKiNOq95Oh1hRMabkJ8UcXTfpcYzXQ6vO6yiy+oxYlhfD7ED6Qsoe+CT3424DPk41kGs1evIeB+bzFRJzUdZpHojIKPNK4E5effefQDAleshBiCewSMyLaV8LASgcynjNSYicIqDWTkMM17jEgmoN4bYqxOr9wivFTtwSbwrlZxMrWIMVlbZJbcLUTswHg3x+OMPy3V40kNO/f3kUdUvT95Xa8Qsz81LTmvxuqigp9MTecDob80qyuJIaqn/x4hsP7w+VFcbqdJIr39FOdywLfxMNSDX9sowLHVCxFhVYNMktiHUIf59YfPBHc7JAvwgSMGZVl647hXGANYYoffMvR8dkrdPz3iXjMG1qyHffe+ttwAAG7eCJsBwGLzXs+e7HHIYVZuIYXsn1BhsP92yzkp1enb1M2w2485BV65s8vrCGJ48of4jv6/24cpYKO5TIosYFcqTDmusPclytKgT0aIi0uqa9AzDdXaWN/h+QDpjIqJ3yFqV599npqLfF6qLY0yG6jgmaTo2+BtX/YOfTkokU8RZAsU2iuTvxtS61aBV7y+wCglUVtkltwuBBHxRYNTvmgdrMvK+RHWapSVVFWobIrOqLlReOXOZcb0VXxiq9TgjyM/YX+DoiOtGemFlIPS0VUpWEWR1lR3y851tee/wfqORc6zLfN/NdB+OKxEHA0VtY0agute0iGxGXF9K2yA18/jKYHwGvQF5onotfPcalXxfvUmVH8Ynnnz8AADQ2w+ZjF0yBq+TIThglPvxx4EJ2GU8Y8oc/PU7IYreXglIY/89tls/OLDrkNafPPk1su3eeONNAMBNjqlvKlCMN1BzUPdwOkliSKbFCL4fx3e0HY0nxlIdMEq/vhH+RO7ceTVcx+374XMy+7773e8CAD547/1wXephSA1KX+j3lXjlRHW4Ib0C/STsnnrTaxTTsZZkqlzS46GMO8TzsMgqJFBZZZfcLgQScM6h1WyYJ1gi26xDr5ozN6s13A57xY+slrt8oqeZA63RO4zES6NAKEO1/ooZWA8+RcN5zsk4Xo951nSrj5206+9TeWdpedkqFvXQl/57t8uoLuMTS1yHqwOwMhvi5Yv1WHo0KyaIX0sjAJ/exPS7Qa7/3avB+65zfgqisha90dGzsNYdkPG2zbjGgTop18m/IAfi/ltfCMdnv0Bx5ZURyHPg3nVqEjDvXW8TEXVYv0GFIcUKhN7Gqqsn0pLiTsP6KobvKwagiRGTM63WHAyH6J5IWzK8N2KNw2RKfshSQEr3XnGor3YAACAASURBVHkjzNNP/3MAgFtELY8++QgA8ODDoJK0y16X/YG0CxXBj00VkNatiu97V8YyprxXY/EcslihWLUVudUzEDFkL5ExWFlllf3TbxcCCdRqNWxuXLG8uaqglPccqipMHrUoqwYBzHjE2Xx/sIKKN8VJ3B3WJxHTzDjz0sprRseW1xYi0FNWvIBj1jM8fRKQwY1btwxtTEydaMpzKVcetsvMGmgMu4o/MMJecsTDOrWMBSB57WffnvN0buZNfdagH+iwKq77PFQ4Hmxt81jhaDdvhLX/D1MBZ3CiiD5ZkVzHDzgfK4wtvPL6fQClStDT7aAcLPWgTqtuVX9ZFr67trrE74RjtDvhHEfHIR7x+Ak1DFg/L4+o30uhytA0i5JqPXISSqXlsalMT3mvanWhsIAIlqmSvM4+DB1WA+Y85B3GLTZXQ9xqazv8Hraehh6X+wchZiDVqXLMGmN8D2fRbWG6mWkVKVGLC/OoWIEyDcqALbIL8RDI8xxr6xsWPFE7bAXjtC2mEvaI9xNldzYwVra+TlJ+CXU0ZeBovzQtlyfBGRW3lDRQpdLCH1GjUbMgj9pllRLiDPrUFOAJ7y9RNKXfU8l0h18jHFSTy8l09nAzywNdPY+fBIoAXxKsDHbygcrrOGKZc5/CFbrO7BZbvK+GH/3GhiTDA6yv8xpvXQ2ps3X+0S9Tfk1wt0vykKB/s1FHj+fK67qPHBsf6FqSHTAoucUl2MjSvCqHNg50NG+ppQ1tZ+dPvyndT+17SIHajylhr+Y0b731RY6RxUxckuh3JAJTsxWubfMozNsuhW9Ft1aa1B4KclbwRvbJspmHOWZ/urFgquZBc16bqFnq6VYtByqr7JLbhUACAADnMJ0IoivwQc+ghg6J9zZPQAifFVkpyGHSzkqfSP4pTqcpaCKyjJ66BYNNuY2FQhQJElPMRe9PCOG7hwfokOzSovxTi9A5k5iliUCQKMJ2UkPKYWk5ILEMeeX+tB+N2VmRi9JPYVPL8vjzoijTiboMzm2PnjnnEksopsay2zFJL3vPApzfoIdrN9UANhZ2FXJSibXSedtcDhwyxejhDU0tkZKrJZ2kskUj1zFKbyu0Jo8ehlC2RBPSkhRcGljlhnOQZZmhDxOZ8TEK22c68sMPQ0pQQrPNZo2fd+Pv+RitdqzNGZeGYQg44g9o0IuFc4qisMBnUcSoFSZuGgviaDk0mXAMRUw/T61CApVVdsntQiAB7z2JMcbQCe9LrNKeyrHYp4hAw4hME7vqRW2+hQRELVXwxBCCvDO9t2SnlF6S93aTuCxVnnYyGuKEhSwqgd0k7bVNeqs8lcQftMZbY1DpiLLTWuu1WNSidKa8ls6t4KX2t1JZbgs3k4JSkEkIhum2Kd1Cix6+7oNH6u2FgNZ2P6zLJ8ebvKaQ+lveCFToIb317rYorfSgDJxubT0BUBb5TCclLTYzz62iLCIBpnFVMpveUsVpxnx/nIiziGyja1fgTOcTKct7b+lFFX+VJeJsTMt2c48fh0Bhm+nM+/fvh3NKlITIwaTqdb0kD4nyLmHbpeXwvgLT5bq/MFp5Sf6RBFmcIp8mcmImnFOcHhuRVUigssouuV0YJDCZTmx9XXAto4IiiUIMFYmn51cLqLg4I4n4WmmwnW3m3RkJbFEw7X0iAXoGiVTmWVjTtSgr5fXE5/es+YQvZa+OKBqyukaiElOhKlPVVpRVnUNNPQ8pQTWmV64nKR9dgwlzGi1W2xKlJCENi6ALGTTUUpyR+g7jDK0izHWdgpvjg/D+Ftf2d+6zFJlts7vbIZ4hNPScWZNnT0PRTzEheismcyrdJb03zoaotLrGgIWKdxRD0P4Ta6qqtb7QHmXoRE8mujumMEqz0cAK5e71exnrtyfBUY774DC8/957JP84ojX+TvQbVYPTZxQ60RhUDGXkNqLfBlPTSu9lzhkS0PXrPqdCOdqK6GZ/FxVtuLLKKjvLLgQSgHNwzpVPNj65JC0t2a0TRoWFAGSzUtzn1dBYblURc74v7oFKhycSoKBXGTFSX/CpbLGELF6X2zodZYNMNR/pHoX1cus10WElPOp4neG6mo3w+g6LboSEPmETVZfEAHwWF8TITOCErzPMcAeMR6EPGQthzr1D2u/mcvBsG6TwLrUp1EqU8c47gR7b3Q2e/q0v/Xi4NraSe8aCmo+Z2z/cfc6xKJdfzDQQFR9ExCyiD3rsFRYfjfh7GCTcDrWQS6m5EoCRHHyrxSwEEdKwH+7tzes3LA4hMVM1YRmKxKOGOJQE398P2YLvvx9KiW9SYFTCJfv7YV4OiQavUnhUwjLdLlucSypf8S7+xvMsmykljoVGy1ZyundClry3jFdprIusQgKVVXbJ7UIgAeccGvXGHD22S8+vtfU0KQ0tWYDiBsw+8U6HBKWcd/KBvElSnGG5Z5778JDRcXrnzY1QeKOntLIKzntzwWMWsBzQKwgZrK+H745tLR+vYa9cCetr8Qm2tp5GQzdRjIROXLYzSzyAc/aeMhNqn6U8f1/HYv5bRTgWW6FX6VDYpcUJGsrj//G3AQBvfTkggo7mg0gKEv3UPZxOSwFZ0ofH3Fdr4WvXrnK+QtZkje3hu1zLq4x5jfyKgwPdI8rGEwGskuUnUZLdXbb2HqnByMiam6aa7HmSaSnl4cMOJ2RC7jjl6MO5T0z6fsTv6x7HXAUTBhELduY3beXuJj0u7kIsw1eWKWu3GGEtsgoJVFbZJbcLgQTyLMPyyjL6LC/tkjV13A1P+mIae+mSg89c9AwTrGSP2U78SrqNLe33UbYZEyLgOeitFZd4+jR4Z0l1r9LrdFotY+zpiX1EFPHeu98HUIplOMU49ODmdqkTPNuNG6FM9cqVgBx2dgLvXBFkywqo+QQWmbf4gPp118g9aNXjFnCPyGnXWnaV+etNlhZfozfeXA7e9XgSsgQZ79nO98MaeaTaAXp3lVyrCWijVkN/RLYc1+aK9u+2QvxAJeZaT79y924Ya9KiXnn0A2ZTxDDssuxZ7eiHw7Bfrxt76b3dXcsCWQPbSdyeba65Dt9X3EIxoTJyLw4CJeOINJ5th3t4wHk+4VitrTjK33Se/BZ1g4uZWBhQZolkZf3B2VYhgcoqu+R2IZCAR+DqH3Nd1aU3MQ74gjZK5vVPRQLxPiW7Tnl8H23LB3y8jrJW5PIEltaNaxOEDCQT1azV0SCfXNH/Kdeou8/C+vkZPfomPZzW3zlRxTIFNj1PevduyBZITsskpm0sHKO1zIpjJc6X9QTiKtwhyhDTT3n9I0phD0jDG4wl7BKOPaY3bYBsP0bV23Wy/pTT7hPNMb/O5AMaLF1uN5ro0pMLAo05l4d7+zZuADjmWj+30mE1JI3XyqotOKHXNSTpJOEVi3q2iW5QTO23ZGW4VqGqhjD6fcX1CCf8zfZYimzNUTn34gdIOOaYVYldlkdb2/GE41EUxQyTMq4FSQVnU/QqO092rkIClVV2ye1CIIHpdIqjoyN0ycueWNONOERbroDiZ5dFurNspmJO34zlmemAUFdjECdxELKtxFIrZR3C/w05aKPyQY6BB1ZOfzqdlmPhd0z8lF5Cef+bt4MQxcpaiH5n1hiFt4cMuVfvh8Yejx8HUY1nz59Hx50M46yAaQb4EjHVJP3Nczh6Scl2y9t0xFzj/NRVbaj2bv0R54/ZAlYLrjKCP7EMhRiHRA7kADiiHdRrFkcRT0JCMH0T+KCeAJGBvKWJcep69bOwEhQKplBGXPdsQASxyiYmHTYJhS9b2XcYj1GmZsQ5HtCTK4uizJXuwZi/3Xoe61h4Qzkh7jHU70ptw03HIhbKiT6bxsy/NP4l5FwkbchUjbnIKiRQWWWX3C4EEphMJ3i299xahKUS0T5d0ySp/uy0tZDFBLieUn07n+xNPh2XGNUVM7DPPLgpOOXKQHCNJs0DtfLO4upDsfQGw5GtK4VUJtPyMwDY3lGTyuBV2sy9Kzag65bQ5p17ISbwxltB5LJPr6I1sufaNtcaeCoIorFPjM9Q4/pYuWerntMaVnwJSbmJOWdxCB2H2g5k6S1Nwpg6nG+JfI7J8mvy+DlFMafwaDNDIe0GtfLSfI2JOkYgiy+pxTcFJ95LVX5e3QxqSOsbgad/eBSQ5rAXYirLZEM6op+1tXXzzFc3w3cyXkef96xHToIESRW/EuNvYAxTNQ8l90HoVoxUZQ0U9+K1qMGOn2l759IffEpioFkmK2lQew6JtkIClVV22e1CIIHpdIr9g32M+BSdEc+Ld1xA9pvjBgD2eJPnryUNSg09cHfFCKbcTqTWkmvRz8hsLY45pPEJLeUG4zEyeo06vaxQiRz0Hte4u7vBM91m9L+eIAix+dYYM7jD/T568CCMdSyBSUa0NTZWY3qJrWYTyD3UiYRUJZdqNbiC1ykmm7gIWm9ybEIM7aWAQo6HJzx5gzMSjr/UCWMT269PGfmiO8FwwOpIcvrrNXlPxWkUKeea2GJAREriMKwGHsUNNgd95ZX7YV4Yf3jv/Q8AAM+fh9x8ZykggSuUC79x/QZ6ZCFeIRLIeS8klS4UJwQgBqkyW31rfKtGM3Hdy5gIQBwHoUBVCDbI19DvrSimpig0330uRgTGdkWsOOXmvxhZhQQqq+yS2wsjARfC4m8DeOy9/wXn3CaA3wFwH8ADAL/kvd8/6xhFUWAw6JdPuoTfX9a+xxggZW/5mX3NU0klWGwqaeDxXFNVa/F7dR+vgfWEzuhtmg21ymryc/G4qRIrbz+Zokev0VCrKSICRe1PiBSebgfewJtkzEmh1yVLP8U1Vvi5lH/FOjMlJiIArectip7NoJGpmqowmzEOY+kw/rBCxZuptBvEMFQbdSKkTcqDv/5KaCBy0mVun1mWpWZgFKrpS52ZgG4Rvt88nqDTVXMQVkdq7i2zE+fJVZ9Rp+ZBsxbm9RrVjW7eCNmWq1dDTGCPNRu1WsjGCJlpTK+/8RqAEBPY3wkZl1WqOzUYp1F8Rqikz3t1RD2FPaK5rngCUr3i7+uYPAC1vzsiL8MUgpXhmcQ6FnCz7exihuD5XMBPZ58HEviPALwz8/rXAXzTe/8WgG/ydWWVVXZB7YWQgHPuLoB/FcB/BeA/5dtfA/Cz/PdvA/h9AL923rEK7+d52eV5uI1fz+ww+wJAGTEXRz2jN1QL6KbYdEOq1dgh2PjDeh/ETR0LZgPabI5a4xpOmY0h14JDP7Tc8kQadlISUtt0Ru136H32yYhb3aAXos7fOFGMkUeUJxNHXF7bUf0nV9trXaufQQteEfawb4vaeNfpAW9xTSwmXPckzNsKWYyKyN+6GbzvG2++CgAYDcP6+oQeb5n59hZbrQ2IUpbq4fWVV9dwwsC5zZfiErzOpioWmf2QspI0HZQFqWdqw8WYCtfV/QH1CTjfavi6wSrNW3du83g1DBj1b1Flua3rJRLUb01IcZVoTNtjXrd4F6oh6JFPIFSSPw3NXQZsMTcY9jhG/h5rYpvOqmQyTmOvnO0z+4Fel1WlONNeFAn8dwD+C5S6FQBww3u/FU7utwBcP+2LzrmvO+feds69/XnBmsoqq+wHt8+MBJxzvwBgx3v//znnfvYH/b73/hsAvhGOlZ36FDgvv3laViBFC+Kda81veXC+39A6U4wuetUx1/FjqD6cakdc5yvmcJW17ooGK/I8mhSm/qoIvDybMhU5PZNiAo+fBP29K9eCF16jN5DegLyJIs25WH+Z8uusXON+dV5jUzqKLiu5F6ZOE76j3gjr7bC9shy87lqLP5HrYUw3rod1thqyqmmouijJIzbUmJTu4YStvnusOVi9HiL5t195FeM8IB4mJOy6FJnXGl66ClJbVoT9hPn/o4Owzj7qhnW6GtZube1w3hj3oHbjlWsBCYip6QuPJq/H1eL4g2JLiqnUiQzEMFxmLcZwc4PnYuUiYwfiFbS4n37w3V4Yc+/kmOcrswI8oV23mZW9KGuiXRf9xZztZF9kOfAzAP4159y/AqAFYNU59z8D2HbO3fLebznnbgHYeYFzVFZZZS/ZPvNDwHv/GwB+AwCIBP5z7/1fds791wB+BcBvcvt7n8M4P5U5zFdYiemn6O6Y6/OCEeW6dTlilFYPTT5eTQmGb5eKt+F7168Fz6hctNafJ/0+8il186exZqIizOr2o3XiA+b9b90JWv5NroGVoz6ix9tnvbwUcBUTkA6BNQNSS2sjNXjrlOQSZRux8BTbUDR71drEBw+m/gTqKbh/TCXkrTAvihkM2NHIa71eD9fSWQ2IQjECAHi6FRDQHeoESA1YMRFlB5SjV3Wg4i8TVjzWyZM4mQav++EHoW/gRx+HrECPehXXGceoN9QBKowjr9esXkOclRqrJ0tdimCm/Z/0TFglqljivEkfc4noTSpHuib1I1DWQIrJVhGY51a/oBiA3W+VErjZ1fiMpUmFBfYyeAK/CeDnnXPvAfh5vq6sssouqH0ujEHv/e8jZAHgvd8F8HOfy3EXvJ9SqK1efkZPoKRPS3FX2vTh9UiqrnwMSst+KmYgufUZo+g5Paf4AQ224paS7epayIevr4eswXG3a7XmqTZiYRVjMY/8KSPGDz76OIxN2ndk/B3SWwgJqI32hN5WcQt1b1adgEVc8rxUHhZ3gTz7IXsa7HPt3mVr8hZVhMX0EwI6YtZAEXZpHwwdGW/UUlimx19eCR4yZ8VelxmMk53nuHLlWjQf0hNQp17FVJQl6fUCWlH85eQwoBKpBp+Q9ffok9AO/JisvhbRTIeRf7EgHc/bbLXQYiZCjEBlRyYNtU9nHYh4IfztNZXXV+Um50nxjFXGDhr8/SjOs7MT5nl7O6Ah8Q6aREHNZtOi+6oSFFqditXqFyABWaUnUFlllZ1lF6J2ANAa6JQaAGA+0WlrIOutqx1LLUDEsQG9bLQV/Q2efMxor+rfrdiL663cM6KvqkNGlhtWD6D9wxebihrXc4zoDaZSleE6U2Mse8uFY+zvB8/2AdeyB+xFqPWjOhQJIfSHsYeciu2o+IYp6pS17c6mkjX79Ehr7I+YrwTPLoSjaPUgLzUbAGDpRljb1zkffaGxRvC2dcVItMaeMiMyIvvPtACG8PTUikek/RqkyzcaqgMVNf2ZDbAOTfy+dfTlOTakUrwR0FqHrM9xLyAOZReWl5atkvOE51YMaMLfQe5ZfZl2LdZNVP+ARP9S+4s3IO/dJo/i1s3AuBwQxSwxLrKyvGKxH2Ua0tIaJxSbdBryyW9/kVVIoLLKLrldICSQLUQAcwwofccUh2aQAb+jTjq5dfzVepy7Ko9NT2UdbD2zBgkHIeN+enJLeUZP9GfPlIumpl4xNY+veMJEGYqJuAZifIVnsZ702+QNSGlHVYVqF6T1pKnJenEchAgUC+C2mL0WeSTWDDAesbwUPHrBnL1rskuPUIxV8inTEOajRc+vm9OTEMNUGQt5PnpIy3FrW1hFp2IAI163kIDp9fGYioGMx4whkCmpNb688o1boZrwzS++BQBY2wxIQGw+IYZ99h/YvHqlRECskfCJnywVqOh1C+kjqPOxJe05RlVEjqNzHzMrIPbjFWoebDEjJG2EZq0Or+uUPmYW/z2klqoMV3oClVVW2Zl2IZCAc476gHzD1lF6HW1KhJDECrz3M4osPHaiO6cnuHLvqsyrM9qvvvFSBVLeWLla8dcVE9ATfWcneG9FzSeTsY3F6ry5dpMunVhnRaE1P3jMrs0LUPIFrFOuKhsTBuLEav7j+RnPaAEY85FoREq7it6vsiuS+vbpGPJgvUEY24i5+JFVOApxqcpuyGtKukZNpZenXPfEqhwVC5DGoGkdJIinsHllnl/1IpzPq1dDXOOHv/QjAEokILbec6o9bz0O/RHF9x/2B5bf1/2dJH0HhEqLVBtwmuyn+AyvQb0s1V9gyN+AOjkVY/W4JLdEHapdVva9TJiDZe1AWWc7a5q385DAhXgIAKHM1ad/7Jj/IwfKP44yNSL558JihlORLqYSWoiLLUaEwfk4DnjpxyzhCsFhPQQKQvweSSAHbM6h0lBJYxXFtFzGJFRmpQQV6CsbnOhhIAgdvldLCCxWMGTlvRxbkoJUdHMqibCJsz8sYUD98a+zYGh9I075mYCmqLoM4vW4dDlkk1XNj65ZRJ7pJG2PzrkoygeV/RED0T72QNfbyfKQiN0e4MtMY77xVmjq8tqbrwMANm+Q0MWHhIrCDg5C+rPLAOzB7h42JCbCORf1O5OcGklmnstN/fGXaVk+0EQMU6u4vmTWuMTjH7RIU5Iq1zWOTCgmN8eje5GNY/k1OEnzJ4V2n7LkuFoOVFbZJbcLggR8eAImDUEW1kAm0ExWFK6sGIr7UVhpcSnaGD9xDb5pucCnroJygt5lIwd5PKX9EkrnzNjnLoP7KuClstE8i72Irk/BKgmQDhgI65GaC9WacNlh6SsF8eTFZ46tFF6LAU5rk26prbhwasTrHPZiqW0FFuecjd1Dk3kJY0ygq4MziTajMpslst0W9I3TtWpYukT0srK2zMsOY1OwtskWY0IEbb5+xkavz55u4+6rr4axJIE9wXPT+rCriOnE1g6eXlppzX6XjVA4n2p3ZjRlya37+DeQZTmaDGKrJL2UVOc+nihW5LMpkXEeL58WWYUEKqvsktsFQQJA8Hta89ESebH5wIctMMNrV3qy1HuYoIdSgbx0n8fNJRQryEg8yRMBiywRuVSLK3lzK+KZvY5UGtpSfUrTMeVH7yxZMK2rZdevB2kGtTzbZTsyFZ+IoiqPUThRW8GxTkpvyiEpQHrYVTBSAqJhvSyRDRFyrHEmPZXERcpW2uBx4tdpdHcWT6lBiU9uvMZt7dW4rfE6NxkAfP3NN/j9MKaTbpiPJ49ZcDQIXnidZb6KsQjdaSz7e3s4OYnnQWjqmE1N/TTERETgahmNnOXQ0zg4K8l1IQIhUkmi9VSwdRy33puaV5+aKGwaINQc6x6oIE2f6xhGZFpgFRKorLJLbhcICcxHNxcmNxIWxGliClpbeRXViLhjaZb4iZ16eJ1Cop16Qqdilyb5RG8OQyKnDddF51K7NRurj+MJQ7Xz5phu3gwlxgNDCCLNBG+uMtURvUtB0UomSkKqUIkDxhV296UBG85xeBC8qJF9RIOdaP3JeeS3hCgyo2vHGRG5cSN0pW4dzlq+lWEEgxfccM6JtpQNULu2Y675WxRJtfml9x2oQQij7I4ReR2nxfX5SfcEz9narc4YiUrNJyY1Hhc1KQak9uFCp4rjKHOjz5d4bgnfqm26qNGSQJuYpNwUk4y/E2vQG6ZHv0ErZ7bGtNyqKU2VHaisssrOsguDBBZLI81/ZnwBeeFTswhxfMFIHqa4wY0IFUkrM8sGWCyAx0t4GVrfmzimjTWbe/5qHVmjB2JfDiM0CQE4r3ZlyrUHTyCBj421UK5cMKbQo8DHyVFYZx4amonz6hNflHNFKuoB4wkDevwlNgBp05PJE8rzu1TG3AqBZCm3I37XJS3iw3TFc28Rd0W9SykPAMCIRKdnzwPpp3tCUdOlTrSVFxZPomHr97AVF2LzSuAGHB8eYuthKD++yviLvGubDVp1LxQrGE6UTUok3LmfSFeSMGvxOMfkBRxSXFacEROCUVn1dIJc7eAnScqLptZpus+WoVBDmaSRaWoVEqissktuFwYJ/CB2FmqQ6Ymqcl01sqh5FXrET1Pz36Kipp5OMYCUtWgyXcrNl3GNlNZpLai4tcYTJg2e0GKJVroUoTw4CIUud2+HNmTXGO0+ZJbg+Ig5fyKN4YBRdpUuZzOilKIDU/K6P2aTDApkNmpq7kmxT2YuyrVvzJBLG8PI0nmWt1fhTD3LLGKuhia5S7aKw0jazVqCkbPQC2NTwVGfHl50625Pkmlh3X3IDMeNGyHGIiTw4MMP0SMDctihDBjHKRS2Sqn5k5PAk5Anl7cV21Pt74QEJHOuOJAYl/LDTYqt6PcnKbqTQQ8Zr0O/C3EWxkkmoZhBfOF1mWE4yyokUFlll9z+qUQCn8bMs8+hBhVViBnHd42XHqwkuml9mmQNrCY5KViaKYJK12ilRHS8VaS5ZCWK4RcOdkRu+/NnIXJ963rwYMtkzIk/sH8YIv2SujpRdHjmWnyySLfVNq9nVGhty7UuYwViTurY8ujm6JPMRnkaIYVgNUYXvOmLZ+bB5E2dNUbhdzgvQiW6ninbyEuoQ6IkqnNoNofcNqJr0ffb7eClb74RagyuX7uBA2ZLukQLy/T8Wsu3GDO5ypZn/t4rAEpEsL0d2IfGR+GYxUwdquyZKEfy58v07jXGK4YUmOn2ejbXmlTFRJQFWFoLKEWZDYsF+ThWsMgqJFBZZZfcLggScJ9qnb/w2zPfTSsNTy+yxEKPmDLfbO1rMYD4C2XWIY4JZCjbqllJsSLN5OuLf681W02eUJWMqk8gX+DwMLD2umSX1YyzELZCBtqKSWhy2S6zPH7KsUhbWWn9WYyTWgiVNzdiOXBLuqTlvrwSuBg5GI7yM2220jFZ+TGRgcQ7xZSTkIcaxzDHrqagEiSVZJjO2eT6vM/Px6Nw/DfffAvf+973wmcshR6NAzLIXPD0Tbad61CEpU6U0WdjE8UChCAlOa5SbJl4CE0iozrH4lRKrMan4zFqSfWosksrLPs2j88aA4msWIVjxRisrLLKzrILggRiOz3vP2+L+APhM/vXzP/n+fx5UhOAxAvZ2l/eVOysIps9DMqHrVhb2dx6W6Zzqt7AJKjUrizZT+8fM3J9yJr+FXp8jXVlOawNlxmRrrFaztBQ5uYhUdKsJW1yaUKaatA6IYPOeOwxA1DIQIBJyEoZgNyQVpllUIYlV0ZCSMiQAGv6FRsgh0HXL/7+WG3YJA4quTF+f0hhVkmryXtLunxjYx1XrjK+wnbvmvOCx2rx3CN6eDWdEXtRrdslJ9ZXExZVMx/ZmQAAIABJREFUhKp6kNc6EXNV1Zvhyq0l22g6wYDXI12B9ashHrGyGuIVDz8JzVWUAdN3LdZSVRFWVlllZ9mFQgKfFgGcZWUbMr2Ot2KqZZabjiWb0lr+Em0ooq98MN+1fHnMestdPt86mq+HzG+XaCM+pqyuaDA93AEbU2xvb/NalOEIY1Alm+rk1VjEUM6MzclRJ9F8swQ5lMhATVmEpBQL4VY8gCTnn6reZAAa9KYrRDBCMorHqAJPyEAcA0mjXWUDlNyuU7EUSoqTH2AVlMmYFJM56fVNUFboQRWZuo4WP2/oenhMa8DKMRQDZnzI0VBdR5voZUDZ9Al1GlS9KlagKkLby8vYuCrVpxADkBqUEI0a1UrVKjMkwNmomo9UVlllZ9kFQQI+Wc9/ukxB2nw0alEuj5wlHtpy8YmUtFhVQgyJ7p+tkRPJ6VJDj99jxVuR5/bvclwxc1DvyuuksQOZqgbVuPQxBTLFDBQrTYhBVYeKCWQz9efz6ERmJXzR2FzC2iuPFdcANBg1V6RefP+mauEVNU94Ay4r8/jLneAlVRthUuTydHPVk7F0+xpbwClzoViK2oILGbTIzltmDGW2DdqTx6EdmKopVT1osu/juFpUbnfsKQyqmgt+vES0Ir6A5mdkrMd+tJX47N17oTnrjds3ce3G9egYyn4cUt/SakP4O9Jv3jJaONsqJFBZZZfcLggSAOC9ebA5HJAgA3fW+2JqaU1q+n3y7HH0XxFkmanOaG1nrL9YVdbWW2o2yteFRjctOQVCBGnmQVa2shLH20db4/mT139M5Ry1ytJx5RlOur3oKLk1WMmQiP7OJe7lFcrYiWTNOY81oQs2H2mryWdAI3lZEhle87g1ZQ1SlOe8VfuV2RQ1CG1Hx7SKzaSWXx7e7mVyCsVIVEtQy8r5CLuHL0yn3uZOjMExtQq6RFn7PGddtSTcqOdKmxH7ZbY8a3P9rt+Jjttl7YCUh4S0XnnlHgDg+q2ATjavXpGEJLbZ4EYxoYO9fR6bvzNjiAoZZ7NDXGgVEqissktuL4QEnHPrAP46gC8h+JJ/G8C7AH4HwH0ADwD8kvd+f8EhymOhbJaZ6vSXlrABE6+WZZk9URUZryfsuzQnb9+1ta+FrwGU63Sf8P9TlaCUm+gy4+bNaA0g2UcquzwX4wtTumu1EVMPBXHf1eNgj/zyPteT0qs7ITtN6WGrAMzLjIUhokRHQWt56dqVnp/eWtkAfr7K9bsq227fCWvZNXpENfrY5dbagHPd3mw3y+pB8SYUG6GHNy09fkcag1bhSD5/VheLMeZ+WGyEEy00t7cfENXDR/8QQIip9Lnefv70UZjbffLxiQhqzP/XnHLwqrkgQpRmwXK4/ntvhB4Id98IOohNjrXPe9ng2G5RNUpKyMfUiKjXGjhhg5vdnTAWtU3rkefgk0xNXheTMm6QssheFAn8FoC/573/IQA/DuAdAL8O4Jve+7cAfJOvK6ussgtqnxkJOOdWAfwLAP4tAPCh4+TIOfc1AD/L3X4bwO8D+LVzj4dTYgGpXh0ts9gBt3kZwc4teh32FXtMT0VTfjG9Nq4HIRWW2TPP1GqLt01v1eQTX+uuaaII433ZGlw8gDRjYTEQjt8VMQpJ6xPUgWifnXPUQm11dYX7heMob2yNS5PKvlnTqdQRRwhAWzH7rX8D9zONf6559/cCh0FVcH/xL/1CGDOj69/61v8DAHjAtutHZD0enfQtXrPG62hwzV4jv17NXztc09fVrFOt4qTjV1cLubg5gPEHeA09KgpvPQmZgBN6f+fK1mQYB1RVZyanlqk4ItYNUA+IAe9795i8Aebsa2shNnDEysYWMzkbVwLrr8WW8EdkJl5Z5vvtEBN48vgJHjx4AADYZ+2IskCaW9UICFHVk1Z6L1NZ6HUAzwD8j865bzvn/rpzbgnADe/9FgBwe/20Lzvnvu6ce9s59/Z5cKWyyip7efYiMYEagJ8A8Fe9999yzv0WfgDo773/BoBvAEAmAT9aGhMot3GE2Rp9zvYUMC5/XEGVPg3TLEH6vkyKrraGVetovlaOXxpxpb6bg3PJOZO6cFuz1sRSm0bvp3UNZY4/WJ/VhXmf63dlAfg9jVXH7fV687qHvF7lwRtaTzv1FkR0XRrr1WvBU1n+m3u+9/73AQD/9x/8AQDgq1/5KgDgR7/0JQBAmxH/J4+fAAD2dncNnXlqCg5HamLKWgDGSAoipU6b2oGcXjn+Zit42YycBVVbnnS1ZXaF74t3IGT20YfvY42eW30Np4OwHi/6Um5mxyDekwHHNkb8G735eogF/PS/+C8BAB58/DEA4A/ffjscnxyFH/6RH+E1hHl8shWQyAGR0v7+gTEex8NEN0G8kHD5lsnS+0IIOvYiexEk8AjAI+/9t/j6byE8FLadc7cAgNudFzhHZZVV9pLtMyMB7/1T59xD59wXvffvAvg5AN/jf78C4De5/b3zjuXgkOc5rrKnnLyN6uHlzddZPy0vf8woedm6sEDZMdreTMfNc/K1xpCqDSddilW5JnabVfiN1L+AB1LtwbSYq8Rz6bInGYuNQTGCpK7Bmg17cepZ8851eK0ee3XL9Vtkf0YBOUFZeXLdNj/SajQuw+nqSIprqDLvj779R+G4jHbff/U1AMAyswbrzJNnec0YkWIVqlJPa1rTfeRY+1Q9mrLmX2MeEEE0EsZgigCEPBRN33se8u69o0M06uFYy+3wW2uqjqFJtEYtxim9MWrhetVjMM/DubusHfjuO38GAPiElX5PnwbloeXlMJYVxkHuvhIUivSbf7YTfGd/MCi1FDln0qhM1az02x8lalBttmRfZC9KFvqrAP6Gc64B4EMAfwUBXfyuc+5XAXwC4Bdf8ByVVVbZS7QXegh47/8YwE+e8tHP/SDHyWs51jfW8dWvhvWjuPDvvPMOgPIJ/kM/9EUAwJMnYT15SO292fW9csAlR/10/nSKAIwjT++gdZQQQKNxekVeqixUqhwX5kXTfeTRFkVt88TzzdD77Drj7+v9uG7c1IFO0Zqz6zfmW5KS0H5JT0fTRWTmwVEUv0QxYexHXId/73vhHu6yZt+8Nr2/L3xZx8GYhrYNKv6K8Wcae1wba+2rzM+AcRn1ArBrELuRakA6zoSaAN3jEHX3kz6GJ2Esh7VwTGkLCikVVKsecNsjVXBIsmKTyAe8h48fBb7BM/IkdC0bm1IFitmg0jjc3Q0K0uPx2BSKU9Vgl9YI+BKFAkBObYPRKO5pmVrFGKyssktuF6J2oNls4s0338SdO0FPf4Ua7/IWUlG9wtzq+++/D2A+119Mp/MdhVL2YVJ5WPLr40i91lPaCilYh5hprFpj3WSlZlP4ucyDedNEzy/l06dZkRTVlBmQuPqwlmgamsbcNNH7mz1X8lpjk7pykVyDPL3OKe8klp7mT/O8u0uWGz1cWlFZrzWMc6H8v45xhXN8l5F68QXAWJC09lINCZnmoS4kJGTG+eiRG1JvkYHYbqKgN+2SsacKRv0+RMIbqApQNfy8hhXW/N9lDcDychjztRshmyIOxyr5FYo5Kb61w1jAMWMD42lZ21J2x1LcJvHhCR9Ev8VU3zC1CglUVtkltwuBBDqdDr7y418xbyEV3ps3bwIAVugJ9LRUhHWS8P+LopjTtEuj4NkCfoBqDNIafO2mLrH63sh6zlFfYByv2wo/kzFI1vRI4hRzFX3aa65KMokxJBwI29uOQ20+W/ZnMymGNMovdmacyRA3XrGDBrMjijOYd6rl0eemzDOWrl9Y89o8QmPKLQai+IuOqc5LBfkW66xTUP5fsQBjiUIZDqEYzo/OKcQkjQNe6xo1++qNuhVceEbgp+zQNCFDcMRskHobCLXcuBV+q7ekA0ANgNdfuw8AWGY8QnGsPSIkMSefsTLwcP8g2r/X72HAMRRWLRhX26aZLu0n7kozyTKldiEeAvV6HTdv3cR3/vQ7AEo5qJ/6qZ8CULaLevfddwEAXQad0oakLnMma4UEduoHYlA7Sx4OIhyZACb/CCDSURwg0x+9JJ7KhwTPmmWl7sQp8l6zx/LJ0mQm5zlzBTM3We9b8xJJUjN9mVxbmf5zVqRlSxMtZzIGnbL4QTUhPK6LyktKqoZoyyXOX5NUX92jAYNvojxLUKW8LzMP2qlEQphuHIRj7B0847lJZdZSJNVjS5d69pT10dj1MLlOWTKlYpfWVtFRS3E9QEZxya/ah/UZnMy4JLnJP/olypsf7IYxP+HD8yd/4s8BAO5cDcuCDwjV+ywKmvLB1uS83L8XlhOH3WM843K4N1CJeNzm3ZHYJUFRE7jhPK4sr+Isq5YDlVV2ye1CIIHhcIgPP/gQj5X6Y0unTQZZrhKuPXwY0i1pM4VZ+q1RbVPPnyCDUj4sLpApJb4IvRI5LAlXmLy15KbMs3HrY5JOOKKCioSxCQHHJ/C+lny/dG1MMfK1lkmSG7OSWWuIUiKLcsnA6xGi4SfmbRNvqh/KNAm8KnW6rBJaUpXHDyWOqkKbQXRtQifeFwZvRRc2kRGeYzxW805E15cu2ZB4wrlSdHZ4FcLYeUYyEcVYsukEK+1wHVcpVSapsxWKhCCvc0xhrIN+WOYcsVnsJw8+4KnCIB64QBZ65w+/DQC4xd9yh6hk65PQCn20E1KCt1iCvNoMAcX1tQ2TVn+yTemzI6Y0E6Fab/cmzM/SUtyMZpFVSKCyyi65XQgk0D0+xh/8/T8w2SR5W5GFmiRsPH9OYQqlBC2YVQp7WBotIQG5RFjUJZ579pPo/WQNbVJOPJ7WxBYzsOYj8wk5C4AlzTKMarygXVTa4txIR4iGWEqfJccRHbdRq88HG/nS2l6nBCbNowl/xKXadg/o2S1VWsTHk7eS169LonumBV0Zt9HJY0+XUpVVMDVL0ArfZywkafIyYWl3n957Mgxr7CnjFQ0AowEFR3YZ62EsYHUjxA+aFEPV9U3ZHLRNRPSMFN/ldthviaKm+t08Jpr1pFc7IrHrawH1NkgjbjfC98Z5jo3VgEJKQZtwLDWh0fsmw8Z56bQ70bwssgoJVFbZJbcLgQRG4zEeP35sCEBeV8hAkXytpa2JhD3pZxpgzJUfn0fEOc+EOujZlBJMUoYpDRnIS/kwnD4mK/Sxll6xHLpLzj1XFJU0T9V85EkpsjzEYFCbSy/JNH4TOzXBVo1RIpbx/kIGotdqXuStpNZWNh9RqlbSalnZWFVp2vz0n6VQhmTWNJg5gRihkWlyjySckgnFsSisxdhDr4chUUEN4TORhabTQOKpNYL3bTALot/eEYuUcmZRlhiRX11a4dg4D0JEKgsW9Z3XvL4ZGo1MOO+jyQQ9ZsuOD0PsZ8jmpanAqEI/umciX0kWf5FVSKCyyi65XQgkAO8xnU7nhD7klUx2i1Y2xEjX+25mH23PRgSLREXKdXYYg8hB46TJZRk04GaGh+BmvF00KJq4CXo/bdVVZgsSJGAFQ+GV1vyiiTbVAINIQ+W9zjlDB8YLWDAPNsYkEq/2WOJuKAItya6DA8med6MxlvRrrdeVHfC2ps8N6HCN7+Not4nINmIPl2Y0hCi11azX6bWXl8Ja+cpa8NYm6Npp44SRd2cZG0q0kZIggdAu5cB8IjQrUZJ2g0ghn0GpANbXgqe/wdZiE/IOJLJSZ1agzu/v7ezgYHc/OqdaoznLDsRZoyXGAlSSPVQbtwVWIYHKKrvkdjGQAGJPvaggxCi/iQBI2eRyfq173so/FRHRsSTcIEagyYepoGOGGTg75jNjDZZhkJS4Sn0V7Y/X6ymjML0qnaqU+Aom+Sk1J+lzDTkcDm2dmCWy3BKisPboNteIxpoKjar0VfEbcRZU/GXFTRJnqdei17M3SHM+JXPQ1tHy9CBySqYjnftshiE5a22y+TaZ819hWa+4IHmnhaUmeQAsuploXliOq1Zfo4niDJJbI2NQ8udlFQ/PLq5I+P7KehjDKz8WmIEblB97+jRkwLa2A29gf28PPaKqgr/BzI6YZIt4b1SAp8KstMFOahUSqKyyS24XBgnMWto0M/WDabPQ8/392WcDZkuB4wi0EEDaLDQt3ki9UNA81VpeSXXJk+uYBWxnzPAAkjiDnTPhxpvxpYQzJUgpnr7WzlmW23ra6i2ScRvqmJvjYBKoePQ45LvF7lQjjL48aFJgU3pnZgKswWlm+xRF8MJDnqNI9N/L+Yyvf64GI2FWSoq7kTQtEVKQEEjuczQVX+G+Q16P5nZIpqCrMcOjJqrrYY3vrKU570WfkmaKJfH9YyKH0Q1mI4goBjzf0ydBcPT46NBiPXMZnUS0pt5Uy/aAcJS5yBfUrsgqJFBZZZfcLggSCEy/+XbZaf1cMD3By/bi85HtlAmYeo+SfRZHksttXD04NyaL4Mc5aiuRnZF8mBrLMNnHmpHEzTGK5Amvk82JpPJjVehpTa2EsdaKxhuo5Qvl0RS9F8PPKtK4n8QtDsizf74XuPKqSmzUGtE8WAygEWcqTBAjqXQEgBY9mDIQZYwgRmlpZsbqPqYphx7RWOQ5jxVlb4T31xjfaOQZ6hJHYbxAJebtNrNEjAVMKI/eYCNWXf9gwKwBkaRYidYyjNew9TDUDAz74fO95yEGsPUkxFb2KS82nYxLYRxdr2Uu4qY29SRLovkRElpkFRKorLJLbhcECQBAWetevmPJ9/BaepQuFuKcdfJzElz29Iw9+3isij6JgMRetlwrIz5Hsu50CRqx80T7xJF2O0cm75mcIwVAJiCa1EWkgqNZ3DDEfKzVWhTwfhwfI5kva4RCLzxRM9QB2Zz0XKqDqPFeqJlqytsXH6CkSmhexRLMbZxlNWjcVFb3RvoBkstSS3KfMiqT69c5JdG+RwZegy52zPX+SqdtzVeaJuHF8ZJd2GnoTyauYJxKDpxbJz5/RvZejdWnjNdsbwVhnD0iqp3tkBWQoM7EJOG8sS6FCNLK1rRZzZBNacTirNfP/jOvkEBllV1yuzhIwJdrNlnqZVMO/mlZATlNNRg12e1EEFReI0vWpi7hC6R0/UWSYXNevJiiDKwn4xXHXbUS4usnn6dWIiOeIkUaieyYsR7lSYuSlWlqQ06KSunJOEa1tko7tSYopcAkGos8veZbMQEhDYtc542y2UjSNETxGSGCFvn6VlOhnL0YcT6eH9mYXI/CsemIxVyC7U+CNx6etNBQLEPjFOKxRq307EKjU/02Ofd2T8WrED+AmSHGBMTiTKXhVBFYy4X2Zuo16OknvHcTaV5IEk4cl+k4OVYVE6isssrOsAuEBOYluhex8NL1uawoirma8/nTxN7zPCvHEJ/SW5PM5DwzVYX6bJHGoHNay8atv05JdoS3EwnyImHxlZz7JG8uTzGTM/GFMhNiK8Z1DvKERnFIJNWlReilYmQoLb7W6TQesyL+0gjo9/tYJ3tOCjjaivloRZM80oTIQV41syrJfnzdiRahrkUMROVvFCfqD4YYZxyf2s0pdpERleRsTc57lgnp5PF86RaKcTqUMK1iRqw67JCHUtf8cSwbm2FORpMJBlzjC3UJhYwUK+NWkvO5JAiFSrKzf+sVEqissktuFwYJeD/zxHfpZ/J82sb89tP2Tc146InXLD8/vepgkRKPTyrcypr/08YtRJBmM8TfP50ZOXcNyXHTVuaqHpz/Htf3xbRkrhVxxqHUQ3QzI4Mx6LQe7Q+1Xh/Fg9JxtFY2pSGuwyXzXYvZet57a7mlsd26dQsAsMnaes2fJOkt5855UNu6PGmKOuL8lNwHIiIhKI5FTVOLorAbrOrI3OI3cSxJugMF+QBt0xfQ9REppPUiUkg2wWClTRCd5xpViY+7XYyEiCh3XmYe4t9oXdWWIn1K9emcX1aFBCqr7JLbBUECHrN+sPSUZ3vrRV7/tO+kjn6OK3/qmOZ56DNHjo57atxijuMe75ty3c+LU/hETbdFZV81qlDjD5lVKZrOX2HoYTyO9f9bbPFlCr+KqNM71+nhJg0y59QM1MfexpRvvc4Zjlc21RSSII+/0bCsgHoVPGITT/EB5OkNxZhisVqihetsMJc/Yk7ecX+hECQNWpXxEIuxVavNRes3qP03YP5faEQq0/Lwq6xQVM2JIw+lwfncYHPVug/3KkuyLiesnBxz/o6Py2a7ylDMcywY20gUpYQ+MiGec2prKiRQWWWX3F4ICTjn/hMA/w6C2/wOgL8CoAPgdwDcB/AAwC957/c/y/EXxQjK88f7nfbZovjCaRyD2c/nvfIiOt/p542On+gjKJ+vll/GeJtDFaefS3GIeS2EJH6RDm6m70CZrw8eXrXnqrCb1tkhhwy2vtAH4w7KIqTtwdOTG9oxXr/iGay2K8ZlxNwyO6rHCMcQatG51YdCPRP6YunxpOpbqnkSg64gGpGSUNlmPRy/5hxanI9hn2zE1Vi9SCaFKdX0q0HpPTYiPWZ15YTsxCbH0uD+kwSJiS1bp1cf8XvtVtvaiA3FEyhiJORMm5JIQUeexnGfRfaZkYBz7g6A/xDAT3rvv4QQS/plAL8O4Jve+7cAfJOvK6ussgtqLxoTqAFoO+fGCAjgCYDfAPCz/Py3Afw+gF/7NAdb7NlPX9eftYQ+jwbg/ek8gkXag6cQ+heduTzOHCqIGW3zPQjTMcUXYc1Wa/H7Wm+7STyBp6nuCjXI42utrzx1i2q5aKrGHuX1ABhMuP5sKEbArSkwxZV/Pr1mhsWVD/cTD+8D2hACmBbN6HoV0xizyrDDGIjQy3QSo7S5TITxCEJuHokmn2IEo8kYTXp8VWb2eifxscTWU0NWHmlAnQAdWZkK+fuyKpWdi4igRrx3qnFRZyI/YBXiFMjJShQ/QGt8tY3MxBNQZWOSJcBcJWxsnxkJeO8fA/hvAHwCYAvAoff+/wRww3u/xX22AFw/7fvOua875952zr39KeJ7lVVW2Uuyz4wEnHMbAL4G4DUABwD+pnPuL3/a73vvvwHgGwCQZ7nPsmwOAZS8/rOfVWWUvVisy3e245471uKYwHlW7jff3SjZI+l7OPvN2W05lLJ/HwAUXMuOh/Ro1reBR01qCGq12hyHP0eSWzaWYTwUsQ71Wp4uz1ipRu+rPgTjFBkoZpDQ/xy86TaOknuXG4CKW4yrZsAtB1ZdRvRia2R+r029v9y4HDzPQFWX8UVOiqmpGmX1MIZjqigLdYiNqTjGRBF4IoedZ+yVwarKgu8bY3AsBuHIzjk7xjZ1CQpe66gYYpzEMEzf0u5Z2DYYG+hwrMZxeIkdiP4CgI+89898qE/9OwD+PIBt59wtAOB25wXOUVlllb1ke5GYwCcAfto51wHQB/BzAN4GcALgVwD8Jre/d96BnCuZfEAZebbo9ym6AbM225017WJk+yxSLVro4M9b8y/6ng1qpitRvC52qee3GEF8Drv+pEefIu32hBdHPskqaN6kRtyo1dBkRZ55dOOf8xjyytx2ycc/IWttYkxJnDo2dUa2nhB05+IVlKpAGnrJEfHWBpE581rcmUnorN/XRISfb6vFHHwz1hBsNFT5Rz4Bc/EH02E0lrIOZILhiGt9zsdJFnvTVPVJiks1orL9g5AIa1FHQOzEMedvyO7MkwSlWb2skKhQcOEx4LGH/G0LQErNSPyQNhFAyzQh9LdwNhL4zA8B7/23nHN/C8AfAZgA+DYCvF8G8LvOuV9FeFD84mc9R2WVVfby7YWyA977vwbgryVvDxFQwQ9gLkYCi5L8i749U22YVh7ak3vOsZ+9xl+EOpJCvpkP5t9P6//LY5997vTyZ/sqzP7DJ95bMQjrTpuo69brNeObK1+v1wVVdEfy/FThOaHnGpLpJy9k60ix05xUgWJ1YdUzlP0NxBic5eILIknzIWEfShuCa/pBXwhIHj5cg1COtPaEAGptZhHGIaswGYaI/2AgPr/qKbxF6ZUdcCbnE6slp/0YhuNhNC+NJpGQkADnb6RrSoCo5nXAa/Q6Xl7DKKn3aDCD0KEO4go7KrWF8sbKFpH/gLPtQtCGnXOo1etGoEhFMc4zk172HmlQ7fw/9vP+IE+nKqffypK/1FQq7dNY+gBbFFgs26/HY7LvSZ6rWVJzgRA4c0KGIu3wR6lAlQJhfRXIWGAwTqdZS3Jep/54BLFLqTD+QdZEadbSTimw8UwakX/83HPMPwRQJktSXWPJwg8lzBG+0eRSZGUp/HGAD5PpKOyX849pjfTiZY5llDN4hwyFj4lLogFb8xUGISWnZssCtQbjw1TkoHoS1NYdLcw/xIy4iQhkSh1Op/bE0B//MsVNN9lkpNNUMJF/PxxLPWlZvsgq2nBllV1yuxBIoNls4s033sQHH34AABgQipYBwTh1VKTBJUuBzLvftMCnPNanG9v5Jccvw84+R0rAEWTNmKZrESZq2yQSqOd1E56QSKfmujsINNW+2m2ZV469cypnLUELZwHCmIhjHjIJ9gqdYDJLoY3nWulFUZM7bLRZo8RXr0cvPfJ8TRTTC8U8CqhNeG2O5c9NXoNasjmWAY9bY7tOIYBB2oRmEtN9teQQJFIwTsVPaoNuCEpXuoAYpxSkEImDM1m1DTY6WScSaOncHGPDx0FNUZqrNmSVVVbZmXYhkABIGBFpRCmwwtahChQlhBN9+1O4dXmgMlB4dtpEtsjzLyIVRY1V59KUpx9zfvw+2Wq/9B9KBSoIFwcCjRCUlyW3PXk4pqx6al7K9fXYWqOlQ/LR29Z23bZMpVnALy4CUoBskhw3zzI4ruVFkEFCitEYG80wxpWVtXBMa3qq9vHh88P9IFKyxDRlncG2Oo9rMlwKcvJ0jbxWlh2TolwkBU/aqoBIJCClVCeUJxMtepKUL5sEfiKKmiUxLM3rcqeD9XZAAB3GVXKVO0vajK68mVyXScGd81uvkEBllV1yuyBIwAFw9vS7dfs2AGCDApT7e4GAIcHF1157DQBMoHJnJ5CyTfJ7AAAX2UlEQVQSHz16jCXWkbY74Uku4QVJVUnK6p3vvQPg/PXSD3YNyatPUdqLU/azCLo1NLEvRAcSIcfksBk9tmW5JK3oYSfjsZUGq3X4UOtmnUEklQSdZIvyliJPGcEp9milw4u9++zRTdLM5Lk1/tPX2VbMwyWxWqZNJmwCOuJamFmSJbUSq7Pk1kLzimuQAJXnJqumOXfW2IMkKBONZcxD506LtaZxWbRiL8OJxFjUSiyZF05fjanVlaUlyzQou1GHMg8qHOI8MP4CiaXwWM2qIWlllVV2ll0QJODh4fHqq68CAO7dC8IMoppKNOK1118HAKyurQIA9tnC6fbtOwCAZrOFldWQO11dDftIFkpr4GVKVS2SJP987ZxMQkoCSvYv5c3jsZZeN87Fp2dTRLvMBIysQMZkxoQW5ghJMSIweqs1N+U5RUzy8ow6/un07XSQhffIJN+dXJfxIES4Scp71cBUfGMDVnqtnD3LopcoKDqhWKra2eUzRKCSxKMYCFEKx2txBM6PSn+hlmmGBHTzOL+KMdiaX5dYFi8BwJDzpm0ry9DgoFp07Q367kwNWsmnGPG3rj/qFq9XMaJFViGByiq75HYhkECj0cC9e/ewuXkFANDthvbOH3/8MQCgzujxG2++CWCmlJYe4s6dgATW1tdm6Knh6fjsmeIFQbzSGpCmrb8W2KfJPJz6PedmFreLzvHpkEJqpTy4Gn/wnPq8Fgtw9tmmazga2trVxinPNNfzVNwDUm9rKtYJOWtxENQirMdmGl0TEtVaN23OEh83r+VlmS49tLJD5qLU0ozXI1RXIqAYteRq0sHXTV5jrvU5eQMFf/6ZpMfzfE6qzeIu4mJompSLT6L70/RyjctRXq/ONXseZcLE2DwmiqlPChMrrQmVjcVdIENQbdtUnmzcDsYGaiUl/zSrkEBllV1yuxBIIM9rWN/YwPUboeHCAcsx9yjvfPPmTQBAkxzyHXr3LteGnzx8CCBE+tfWQg5Zks0P+ZmQQCr7/fkTAGcO+IMefGHRUlxTIIlsaxpqAhcUqFBOfhKXBU992VwjZU6mI9U6WZ6/Q8nsNhGAtirzHTHrYIFonyABk8vWcQOC6CwtWVajfxAQoLCKmoWofsFaset6uSZWdkTXoB91k28IEYCecsQsQ9nynt/Icis+MoESotDMipPq0edSejPJ9aRkpTBuAveX31WRFHFcxvMOGMdpE1LkHshVz8D7aXLwEk5NClYmlrEgZ2EqluPpViGByiq75HYhkMB4PMbT7W2LYksE487du9F+u/shG/Dk6VMAwIOPPgJQerNanuMLX/gCgNIraB1pJaD/2AQNT0EBSY7cz7Hw5tIF0bFckqNOG5COlPNXxH8ae8zQ6k3cg9MlwjWZysWrOajacqWlworUKwZjh0vKKOv1uK5hZSVkbzrLy+gfh3VwQ2tX1TdMxMaL2YdpOS8SpKQVcF3rcEX86WUxEavPavpsEsZc+48lqT4Ix6irLDuRZldWQN7YWoPx8jWWtlqeE7WIcagaDTEq1TDF1v+TCUYqdU6l2sriEV5FjEamRBDHQyKfBVYhgcoqu+R2IZDAaDzG4yeP8d573wcAvP76GwCA22QObm8H8cYnT54AKHkEa6th/a814vHRsXmq3knwULNy2y/TUiLdaY1JFyGBuBJgdo0XeziXrKv1TeOls/WVd5PZj2EtR9xsldrp9Rcag6r85AHTtm1i7x0eBHSmSr8sYf9pzMsrrIBbCyzPDvkag8EQR4cHAIC2BEPFHPTKCsSiGs4EaJIKT7sGVvgl2QP9FsSkbLjw+TLZgO28hr7nuttasYt1SUETZiaERkzCTSIqRAZNIim9r4wF8licRTBlPIpbv5scWzEtuQcJejOOgdiHhgAYG+D8DCgMs8gqJFBZZZfcLgQSmEzG2NnetoaUJ/Ti6+uhGaTyofv0GE+JDNboVfr94JV2n++Wcll8ena53vysugDn7Tf/8cwbSTFguoY/76CpstCsoOrscZzl0bV2phe2nLeG4cqIuzXPiOsU0rp/jcGUdhi3OToMbbb6fTbnUD5d4qD0hMoibG6E2g3JjQ2ZTegeH1tbMGu5revP1d6cDT+KpCrOuP+cNs6TxQR04dPYy6YS3StEO51aA45ec0BXLUalovg69VR1DcpYqJGrqjITsdcyPvH/t3dloZocVfj7/rtMTGIwcYljEkyEuETBBRGjPoi7IuqLMIKQB8EXwQVBM/ggvvkgouACwX0hIioaAq5R8MkVRUbjmEhER6MTNYtEnZn79/GhzznVdarr/28uye3Gvz649O3u6qrTy19nrXPseffoLN2b2UGWuSQyRJksV7Ix7Hvw9QxK815bRdjQ0LAKs5AElntL3H33Pc5177239/HfY0UdPcX2Us/3x6OeKl0quOk81CK71pYi3x9ipqJqDsIVw0ThoWw6Ln1Y356IM+jAtvbdwv9SrsJ0fQpiNO6B7NqtrdzzYNzTsv/8S6U1K/IZk8IaTRbLYGXFTQLw2AWVKLpzZ730l3FokwiMk3dW0qtTiSBwwCQBKNe1pKdmNfd7yFeMpuep35ec6+t+IUVQJutL/k7Sd6Y2EC8SmxuFkqQFvQe1MdiaAo8X0MvCB9yJFLYj8W8vtRn2Yc8nxVmslmabJNDQsOGYhSQA6MQXuE/k2j6ruj4W9CZJfbjFPXCL6vhFhqABXYMOLYuPL9bOMh0HVKSCEFQWXfQpk28h1uTXOff1Ihqxw2V5M4mdZHSnFYnq/1a2YinC/f6Utm2Pu7Dnm8cfpIIh/WV7VjLNfN2mn3dpBaJ7R8zirs9arHy6PwCLZchLqVnBTosgNO5scRImURon/a/q33drQdT/LHb8AXkGIB3S1yeErZdjs++iyMOQF9Cxm/SVkyoRnGOIOBxk3PYE0d5rbguxd9kx0h7cURU0SaChYcMxE0lAgK5LFtPIXd26nW9TyvacG+VdV3R0n5gDy49cu+Krt+skXJ5qjO7f9iDhP88oFHT+4haiJMDwoPJl+YCMSTx57IHFxBsNLpV5+/y6lPMgl14sV5+dN33ci4pmnC7qz+rXN7JNMti2z9UyKinnVxZpGXTO286lEJM+vESd8lRb8eelyaVLVnzn+Daicn7bt+jEUCrP1gT4K2C+jbB783V+JmAOd2uSYOUat/PsTxBokkBDw6ZjFpKA6T3JCjo+d1VU5EE+PNZN78VF47Q4Z3SOt8iaR6/DqnpltWpFkbTiuGR8oPDhD639K3sckX48K5Gva1cLurHFYARJsQ0hl56V0zIfP8xWoPr5jq0xyOMMPLeebSFe9twj+9RNEIt22v1Hn/v5Otb5GnF4xMa21ZRKq8Xrx3yJ7m1AN4jNUA4dpE2XCDx3gW49fh/Z1nvLnQYDSRTab8BAqvO+KtmrXXIMNSLSdrUs0CSBhoYNxywkAUB92EVUn27TkbCv1yK2G3aStylOB+9BnPGrXoW1Oj+HLDu/dM2VqV3OIRN37vc656a5fp4iyWIdPHpk36767e2Zn+vOZrQmgSCuSLTy2KGuQHhQReYczwaVl1XvIGktvm3tnHsuNE7fsvvoWLt6LxfqvTwMFs9vrpxxG4vnNjBbA9I7jxKf20qQt3WbgWclzi32vt6zIoFa5aYUh5C/W8+3iF5CGbaJX2WUBODt81oHNayVBEh+iuRpkicGxy4h+V2St+n24sG54yRvJ3mS5MvX9d/Q0DAt9iMJfAbARwB8bnDsegC3iMj7SV6v++8meQ2AYwCeCuBxAL5H8oki0aFfg86uwdLMwJWr3LmIth9EYFUivtJKvdhDPmasnCuBO6fuhtebByHGEuzfczAcO4XMh7gAHyf3YKSzyZJtqwOtPqHVIaiR5HaNkJsxSQJhTOO+xs2DLWAZVsQJxO0uFkVn9gkO8hAa/UDK0nPhwzTf4ZZlEe6lmfvPqO6/Y/UJFtn1ztWtcrBZ+IXpXLA/WEagLefguZIvMblgEeQRvTK5lOc1HeO6CJRRsB6Tofu1NQWC/X1vayUBEfkhgH+Gw68F8Fn9/7MAXjc4/iUROSMidwC4HcBz1o3R0NAwHQ5qE7hURO4EABG5k+Rj9PhlAH40aHdKjxUg+WYAb9Y9QJj0qainm34UmO+oRBCsuYMBIwV5u5rEEHPyFbPreBwCB/r4wrnjau9HuoVcv4w1CMtViMY18jXuQwkA6DMDW44889uf0wy/0VrNMKZxOuaMyhsuVf/0VZxdfp1LBMvwvGThVY9MAuiUil1d52/ZfHaU4x/R7QXn9dWmLGfgv//V5yj8t62QfPjDtZ8tv38AoI5j/dl5ivgzs9WQVptgkQoSKP25dOYnFjnfjvaI4uux5+5rDvQ6e16Uws5Q8ncbM5dGZPRoiQfbMDj2uxz94kXkBgA3AMDCrCoNDQ2HjoNOAn8jeVSlgKMATuvxUwCuGLS7HMBf1nVGEAssSm6k2xhbHlzZeV+BoztHjqv9vH3dwpCPFrh4tPyHbkSGdgMby7hCnoE3xhykq/J968+5Us0v4iSpJODx6wvsnbWqRP0qQKsE7JmA7FojyUg1XdjiJkKuQpcULFpPY+OlMy7f92PL5MVLHtHH6DrLg6B0axXe7e1e97f6BEdU1z+jufn/eU+/6lQsG6/yvnvU3nHxjl6nNgTRCEKP69+xDMP0iEaqzcSerXszlrkE0AW+HFcRRqt/suTr9S4S6b1riWGTrIQLl6KWXW4LMg6fMgn12NN3ZaUfYiXoiIPGCdwE4Dr9/zoA3xgcP0byCMmrAFwN4CcHHKOhoeEQsFYSIHkjgBcCeBTJUwDeC+D9AL5M8k0A/gjg9QAgIr8m+WUAv0E/Mb1lP54BAdBhMQySys8XFnyMNwRHVP9xi3mMeY9dFV6GQEtEUKEHXomRGG5bHVdw/nzsWiiCFJbnvH/XECVn57JcDrhKrsMaN1lYvvutnNNbxl/Pae+WfOWc2p1lyb3f6v2dy9cK7FkNBBcJEuePuQGXyqPOLBP9AKCpFD1L8X/2rK/+hEXxndHKy2f1eZ9vXojOqvb2213l7gtZwD7XXZNKYtzIdv6RmkCTvCDL7Hz8sjxvQIxZ0MUDW1o5eU/vvZOUkdhXBzLvS0lNEoDSaisTz0bPRQAPLwX3CiIW27K1e9HgSPiczfu0vqfBv9EwmO9K/GHGnhj/qSHvIfXLovMYzFMbncV5CZsa1UH1sQlwUForJj2NNNgSYXORJVdf/iEWS20tj2ZIMBp/4F1wHfY92A8hqS1AEq2LlGeWyktVG/EEpHr/9iNX6o6o4c+SlNCNk/my5yFdMdjJApboS6j79lZ4tYsTenz38XD4vuzeLJzbDLdZIpjwj+1a7dPOEsJ4q9yQfN8/Tv1cRJ6NgBY23NCw4ZhF2PDWzi4uvPTKwUR3UOmEiLPkiFMmG6KmgrgQEhJDrho5NhxJdlY2GvZRFTpC+2o7ozWMO2xfVTH6rXHhWMIyurQK95Q/0JxbF+PE0PBF6iNyepcimBsMrb0t7kkLrLaGp90Qu5UO5Pei26VJLwN1UkwS8iQyRsN23kdM4hkWeRWuaOs3HHdpzYyivjx8oP5VVN1t7zt//wwf933f/CLG0CSBhoYNxywkAS52sHvRY+tJQNctwMmCi4IrrwjVHR+jJgmsiFEOzaMbczESvpvTW+iHsWVt7OJ0zgGi4dD1dmKtJFCkY6skUXEBoDBORuLWPEAy2XyiJFBwydzm0QWaYop1lzAKTqm0Wv+eIoyJk3snuSRgEkLi8OF2grQCRtrzeyhc2G6ITDTGtORRSl0ECQDhW1z3Dpok0NCw4ZiFJAAQ2Ita6MrW2T8c+uM8wCbq0cEmUPS5hu3GoxWdd+Ez+WLAVYNEUJUExiUAqZBWLHwNnLIMVio7j7p+pLFIvxas2i59IN5TkEIK4hPni56YQgrh+P2Vi5cqPC2ud44uZ88gsyjtBtEdK/EZWzv7xwbNJQbLICo1D45LBHY4cX9fUxRtA747/k73K842SaChYcMxD0mgE/DMXn2+qnDdUu1kkgBs4q5MhvUUZjWuUbDKldf3VvZxzuaRpcXFsc9xySDeOAsuFef2Sj+DY6UubySN339hdyikm9hRHNC495B+7z1r62MbNw16uY8VsnkWqbwiI/XmGizEruT8scaZBhgVEk7l3cWl7AzPK11ntoPYy0CzX83QE+Jy9+J7yNEkgYaGDccsJAEC2F7liF8TN5C4lGDwb78pdNjhqPW+RHLuQgSr8ZrAAWbnI5eNEkKlnTMjhtNRJ7Yw5Jz2yJWZgvMSJG8Tn4+TEmiQ5E7Q68YXahX36sMmmsp08FH6GNfLUyp26yvcQ2DiaT8+zzTuItoV/DvKvU6FJGnvIFBcxrqPE0cG6Se2Q/2TC598EZIcPsYCTRJoaNhwzEISALCS29f1rvxaorSU7h/O4nSoXA+12TT6oEvbQtQF+1bDTfU+iim9crwydVe9DQOpqPZ84pKCOOSI2DK6L0ERT8unQ7vBSFVPTf5Kkq7LtMx2nPb4bqLUMn4HJAdrGvxg6DzQlpNWdmqouUn8eLiJkSZVuPSaSwCl3WEcTRJoaNhwzEYSIFYIAwdl7oCz5BjRVzSLg/kMnRfA8CizRehvdLatRTrWwvZyEgpWyHy/6C80H/WAxLpp0XQedGDGvkzvLjhahetEI80qBB1WovO9pleHG4+0FZGo4RG4FV06P1omH8+GKJ7jInZaSGHj/RX9ms1h366AgU2kIumse/JNEmho2HDMRhIQjHCXgHVzY83z3yOu7sqvSVxBRhswWlj9+GK8oxVjRC04mQDMtpFzwELXDenWrMhEzSsw9A4kBjbOoaMlPUbxleWux7kvR/4bPz8cc5xjp90gpflLCHaIKCkFCSp2nN4LH7DUuQjPKQamlCnv49jxu9IkqW7n6pDSk0fk37btL2lFZfMVi9V7WHm2oaHh/x7zyCxE3gXgfgB/n5qWCh6FRttB0Gh74Hgo6Xq8iDw6HpzFJAAAJH82lvpoDmi0HQyNtgeOKehq6kBDw4ajTQINDRuOOU0CN0xNwAo02g6GRtsDx6HTNRubQENDwzSYkyTQ0NAwAdok0NCw4ZjFJEDyFSRPkryd5PUT0nEFyR+QvJXkr0m+TY9fQvK7JG/T7cUT0rhF8hckb54TbSQfQfIrJH+rz+/aGdH2Dn2fJ0jeSPK8qWgj+SmSp0meGByr0kLyuP4uTpJ8+UNB0+STAMktAB8F8EoA1wB4A8lrJiJnD8A7ReQpAJ4L4C1Ky/UAbhGRqwHcovtT4W0Abh3sz4W2DwP4log8GcDT0dM4OW0kLwPwVgDPFpGnoa+rcmxC2j4D4BXh2Cgt+u0dA/BUveZj+nt5cCEik/4BuBbAtwf7xwEcn5oupeUbAF4K4CSAo3rsKICTE9FzuX4kLwJwsx6bnDYAFwG4A2poHhyfA22XAfgTgEvQr5W5GcDLpqQNwJUATqx7TvG3AODbAK59sOmZXBJAekmGU3psUpC8EsAzAfwYwKUicicA6PYxE5H1IQDvQipIC8yDticAuAvAp1VV+QTJC+ZAm4j8GcAH0FfPvhPAvSLynTnQNkCNlkP5bcxhEli/EP+QQfJCAF8F8HYRuW9KWgwkXw3gtIj8fGpaRrAN4FkAPi4iz0S/DmRKlcmh+vVrAVwF4HEALiD5xmmp2jcO5bcxh0ngFIArBvuXA/jLRLSA5A76CeCLIvI1Pfw3kkf1/FEApycg7fkAXkPyDwC+BOBFJL8wE9pOATglIj/W/a+gnxTmQNtLANwhIneJyDkAXwPwvJnQZqjRcii/jTlMAj8FcDXJq0juojeE3DQFIexTs3wSwK0i8sHBqZsAXKf/X4feVnCoEJHjInK5iFyJ/hl9X0TeOBPa/grgTySfpIdeDOA3c6ANvRrwXJLn6/t9MXqj5RxoM9RouQnAMZJHSF4F4GoAP3nQRz9sQ03FUPIqAL8D8HsA75mQjhegF7d+BeCX+vcqAI9Eb5C7TbeXTPy8XohkGJwFbQCeAeBn+uy+DuDiGdH2PgC/BXACwOcBHJmKNgA3ordNnEPP6d+0ihYA79HfxUkAr3woaGphww0NG445qAMNDQ0Tok0CDQ0bjjYJNDRsONok0NCw4WiTQEPDhqNNAg0NG442CTQ0bDj+B+J2FOzdYjF0AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "evaluate_single_pic(\"./3.png\", True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is Maokai\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "evaluate_single_pic(\"./aaa.jpg\", True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is Vayne\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "evaluate_single_pic(\"./4.png\", True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "TensorFlow-GPU",
   "language": "python",
   "name": "tf2_gpu"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
